Artificial intelligence (AI) Books

Book SynopsisThe 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023.The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows:Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application.Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot.Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots.Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots.Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots.Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics.Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction.Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms.Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.Table of Contents​Perception and Manipulation of Dexterous Hand for Humanoid Robot.- Dexterous Hand-Object Interaction Control Based on Adaptive Impedance Algorithm.- Design and Control of a Two-Segment Rotatable wire-driven Flexible Arm.- Design and Research of a New Underactuated Manipulator.- Medical Imaging for Biomedical Robotics.- Accelerated Unfolding Network for Medical Image Reconstruction with Efficient Information Flow.- Examining the Impact of Muscle-Electrode Distance in sEMG Based Hand Motion Recognition.- Fast calibration for ultrasound imaging guidance based on depth camera.- Zero-Shot Kidney Stone Segmentation Based on Segmentation Anything Model for Robotic-Assisted Endoscope Navigation.- Sutures and Landmarks Joint Detection Method Based on Convolutional Neural Network for Rat Stereotactic Surgery.- Prior Region Mask R-CNN for thyroid nodule segmentation in ultrasound images.- Digital Twin Model Based Robot-Assisted Needle Insertion Navigation System with Visual and Force Feedback.- A Modified BiSeNet for Spinal Segmentation.- Retinal Vascular Segmentation Based on Depth-Separable Convolution and Attention Mechanisms.- SW-YOLO: Improved YOLOv5s algorithm for Blood Cell Detection.- A Novel Full Prediction Model of 3D Needle Insertion Procedures Combining the Kriging and Local Constrained Method.- Autofocusing for Cleavage-Stage Embryos in Brightfield Microscopy: Towards Automated Preimplantation Genetic Testing.- Advanced Underwater Robot Technologies.- Cooperative pursuit-evasion game for multi-AUVs in the ocean current and obstacle environment.- Rock-climbing fish inspired skeleton-embedded rigid-flexible coupling suction disc design for adhesion enhancement.- An Underwater Inductively Coupled Power Transfer System with a Ring-shaped Coupler for ROV Charging.- Micro-needle Dynamic Anchoring Foot Design for Underwater Drilling Robot.- Adaptive Control for Compact Vector-Propelled ROVs in Underwater Detection: Enhancing Stability and Maneuverability.- Dual-Arm Dynamic Planning with Considering Arm Reachability Constraint in Task Space.- SLAM Algorithm of Underwater Vehicle Based on Multi-beam Sonar.- Design and Development of ROV for Ship Hull Inspection.- Research on Structure Design and Drive Control of Soft Joint on Underwater Snake-like Robot.- Reconfigurable Torso-Based Quadruped Robot for Post-Tilt Recovery.- Innovative Design and Performance Evaluation of Robot Mechanisms - Ⅰ.- Kinematics Analysis of a New Parallel Mechanism with Complete Separation of Constraints and Drives.- Design of Flexure Hinges Using Topology Optimization Based on Isogeometric Analysis.- Design and Workspace Evaluation of a Novel Parallel Grasping Manipulator with Configurable Platform.- Research on Forward Kinematics Solutions of 3RPUPc-UPS Parallel Mechanism Based on Particle-Artificial Bee Colony Algorithm.- Stiffness calculation method and deformation energy of lattice filled structure.- Analytical Backlash Model for 3K-Type Planetary Gear Train with Flexure-Based Anti-Backlash Carrier.- Design and Analysis of a Novel Membrane Deployable Solar Array Based on STACER Deployable Mechanism for CubeSats.- Graded Error Compensation Method for Heavy-Load Manipulators Based on Laser Tracking Measurement.- A Flexible Parallel Robotic Wrist Towards Transluminal Endoscopic Surgery.- Parameterizing Dexterous Workspace of Industrial Robots.- Design and Kinematic Analysis of a Mobile Parallel Mechanism with Over Constrained Branch Chains.- Design and Analysis of Space Extra Long deployable Telescopic Boom Based on Cable Drive.- Extenics Networking Method of Generalized Deployable Units.- Research on Foot Slippage Suppression of Mammal Type Legged Robot based on Optimal Force Allocation.- Evaluation of Wearable Robots for Assistance and Rehabilitation.- Improved Notch Filter Method for Vibration Suppression of Flexible Joint Robots with Harmonic Reducers.- Design of a Locust-Like Robot Based on Metamorphic Mechanism.- A Reconfigurable Cable-Driven Hybrid Robot Synchronous Calibration Method Considering Multiple Mapping Relationships.- Wearable Robots Improve Upper Limb Function in Stroke Patients.- Design and Evaluation of a Pelvic-Assisted Gait Training Method for Mobility Improvement in Stroke Patients.- Effect of Lower Limb Exoskeleton Robot on Walking Function of Stroke Patients.- Design and Control of a Novel Underactuated Soft Exosuit.- Morphology Design of Soft Strain Sensors with Superior Stability for Wearable Rehabilitation Robots.- The Feasibility, Safety and Efficacy of Robot-Assisted Gait Training Based on a Wearable Ankle Robot in Stroke Rehabilitation.- 3D Printing Soft Robots.- Design and Control of a Miniature Soft Robotic Fish Actuated by Artificial Muscles.- A Single-DOF Quadrilateral Pyramid Deployable Unit and Its Networking Mechanism.- A Rigid-Soft Pneumatic Wrist with Fixed Rotation Axes and Active Jamming Variable Stiffness Mechanisms.

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Book SynopsisThe 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023.The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows:Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application.Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot.Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots.Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots.Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots.Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics.Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction.Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms.Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.Table of Contents​3D Printing Soft Robots.- Adaptive Fault Tolerant Crotroller for Nonlinear Active Suspension.- Ultraviolet Curable Materials for 3d Printing Soft Robots: From Hydrogels to Elastomers and Shape Memory Polymers.- Design and Grasping Experiments of a Three-Branch Dexterous Soft Gripper.- Modelling Analysis of a Soft Robotic Arm Based on Pneumatic-Network Structure.- Integrated DLP and DIW 3D Printer for Flexible Electronics.- Bi-Directional Deformation, Stiffness-Tunable, and Electrically Controlled Soft Actuators Based on LCEs 4D Printing.- Multi-Material Integrated Printing of Reprogrammable Magnetically Actuated Soft Structures.- A Lightweight Jumping Robot with Untethered Actuation.- Dielectric Elastomer Actuators for Soft RoboticsLanding Trajectory and Control Optimization for Helicopter in Tail Rotor Pitch Lockup.- A Dual-Mode Micro Flapping Wing Robot with Water Gliding and Taking-Off Motion.- A Self-Loading Suction Cup Driven by Resonant-Impact Dielectric Elastomer Artificial Muscles.- Model-Free Adaptive Control of Dielectric Elastomer Actuator.- Modeling and Design Optimization of a Pre-Stretched Rolled Dielectric Elastomer Actuator.- Structural Dynamics Modeling with Modal Parameters and Excitation Decoupling Method Based on Energy Distribution.- Force Sensor-Based Linear Actuator Stiffness Rendering Control.- Design, Modeling and Control of a Dielectric Elastomer Actuated Micro-Positioning Stage.- Tension Distribution Algorithm of Flexible Cable Redundant Traction for Stable Motion of Air-Bearing Platform.- Research on High-Frequency Motion Control of Voice Coil Motors Based on Fuzzy PID.- Feedback Linearization with Improved ESO For Quadrotor Attitude Control.- Design and Analysis of a Flexible Joint Actuator Based on Peano-Hasel with Performance Enhancement Characteristics.- Human-like Locomotion and Manipulation.- Walking Stability Analysis of Biped Robot Based on Actuator Response Characteristics.- Design of an Actuator for Biped Robots Based on the Axial Flux Motor.- Omnidirectional Walking Realization of A Biped Robot.- Control of the Wheeled Bipedal Robot on Roads with Large and Unknown Inclination.- Nonsmooth Dynamic Modeling of a Humanoid Robot with Parallel Mechanisms.- Human-Like Dexterous Manipulation for Anthropomorphic Hand-Arm Robotic System via Teleoperation.- Design of a Compact Anthropomorphic Robotic Hand with Hybrid Linkage and Direct Actuation.- Application of Compliant Control in Position-Based Humanoid Robot.- Fast Walking of Position-Controlled Biped Robot Based on Whole-Body Compliance Control.- Whole Body Balance Control for Bipedal Robots Based on Virtual Model Control.- Design and Implementation of Lightweight Thigh Structures for Biped Robots Based on Spatial Lattice Structure and Additive Manufacturing Technology.- Design of a Humanoid Robot Foot with a Lattice Structure for Absorbing Ground Impact Forces.- An Action Evaluation and Scaling Algorithm for Robot Motion Planning.- Design and Control of the Biped Robot HTY.- SPSOC: Staged Pseudo-Spectral Optimal Control Optimization Model For Robotic Chinese Calligraphy.- Obstacle Avoidance Path Planning Method Based on DQN-HER.- Realizing Human-like Walking and Running with Feedforward Enhanced Reinforcement Learning.- Research on Target Trajectory Planning Method of Humanoid Manipulators Based on Reinforcement Learning.- Study on the Impact Performance of the Joint Cycloid Reducer for Legged Robots.- An Optimal Configuration Solution of 8-DOF Redundant Manipulator for Flying Ball.- Smooth Composite-space RRT: An Improved Motion Planner for Manipulators under Incomplete Orientation Constraint.- Cooperative Control of Dual-Arm Robot of Adaptive Impedance Controller Based on RBF Neural Network.- Trajectory Tracking Control for Robot Manipulator under Dynamic Environment.- Pattern Recognition and Machine Learning for Smart Robots.- A High-Temperature Resistant Robot for Fixed-Point Firefighting.- Multiscale Dual-Channel Attention Network for Point Cloud Analysis.- Study on Quantitative Precipitation Estimation and Model’s Transfer Performance by Incorporating Dual Polarization Radar Variables.- Research on Object Detection Methods in Low-light Conditions.- Image Recovery and Object Detection Integrated Algorithms for Robots in Harsh Battlefield Environments.- A Fuzzy-Based Improved Dynamic Window Approach for Path Planning of Mobile Robot.- Is the Encoder Necessary in DETR-Type Models? - Analysis of Encoder Redundancy.- Image Enhancement Algorithm Based on Multi-Scale Convolution Neural Network.

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Book SynopsisThe 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023.The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows:Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application.Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot.Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots.Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots.Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots.Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics.Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction.Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms.Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.Table of Contents​Pattern Recognition and Machine Learning for Smart Robots.- Real-Time Detection and Tracking of Express Parcels Based on Improved YOLOv5+DeepSORT.- Micro Speaker Quality Inspection Based on Time-Frequency Domain Feature Learning .- Micro Speaker Quality Inspection Based on Time-Frequency Domain Feature Learning .- Robotic Tactile Sensation, Perception, and Applications.- FBG Tactile Sensor Integrated on Bronchoscope for Force and Contact Position Sensing.- Soft Humanoid Finger with Magnetic Tactile Perception.- Learning Tactilemotor Policy For Robotic Cable Following via Sim-to-Real Transfer.- Electric Fish-Inspired Proximity and Pressure Sensing Electronic Skin.- A Novel Tactile Palm for Robotic Object Manipulation.- Tactile-Based Slip Detection Towards Robot Grasping.- A Faster and More Robust Momentum Observer for Robot Collision Detection Based on Loop Shaping Techniques.- Dynamic and static performance analysis of a linear solenoid elastic actuator with a large load capacity.- Fully tactile dexterous hand grasping strategy combining visual and tactile senses.- Intelligent Tactile System and Human-Robot Interaction for Collaborative Robots.- Tacformer : A Self-attention Spiking Neural Network for Tactile Object Recognition.- MC-Tac: Modular Camera-based Tactile Sensor for Robot Gripper.- Advanced Sensing and Control Technology for Human-robot Interaction.- Integrated Direct/Indirect Adaptive Robust Control for Electrical Driven Injection Machine Mold Closing with Accurate Parameter Estimations.- Admittance Control of Flexible Joint with Dual-Disturbance Observer.- Physical Reality Constrained Dynamics Identification of Robots Based on CAD Model.- Constant Force Tracking Using Dynamical System with External Force Estimation.- Demonstration Shaped Reward Machine for Robot Assembly Reinforcement Learning Tasks.- The Construction of Intelligent Grasping System Based on EEG.- Comparing of Electromyography and Ultrasound for Estimation of Joint Angle and Torque.- An Efficient Robot Payload Identification Method Based on Decomposed Motion Experimental Approach.- A Force Exertion Method for Redundant Mobile Manipulators Safely Operating in Small Spaces.- Prediction of Elbow Torque Using Improved African Vultures Optimization Algorithm in Neuromusculoskeletal Model.- Usability Evaluation of FURS Robot Control Panel Interface Design Based on SUS.- Knowledge-based Robot Decision-making and Manipulation.- Obstacle-Avoidance State Characterization Models Based on Hybrid Geometric Descriptions for Mobile Manipulators.- Performance Optimization of Robotic Polishing System With a 3-DOF End-Effector Using Trajectory Planning Method.- KGGPT: Empowering Robots with OpenAI's ChatGPT and Knowledge Graph.- Robot Trajectory Optimization with Reinforcement Learning Based on Local Dynamic Fitting.- ChatGPT for Robotics: A New Approach to Human-Robot Interaction and Task Planning.- Precision Control and Simulation Verification of Hydraulic Manipulator under Unknown Load.- Experience Adapter: Adapting Pre-Trained Language Models for Continual Task Planning.- Nonlinear Disturbance Observer-Based Continuous Fixed-Time Tracking Control for Uncertain Robotic Systems.- Optimized Adaptive Impedance Control Based on Robotic Seven-Axis Linkage Grinding Platform.- Decision-Making in Robotic Grasping with Large Language Models.- Language Guided Grasping of Unknown Concepts Based on Knowledge System .- A Review of Nonlinear Systems Based on Optimal Control Theory.- Design and Control of Legged Robots.- A Locust-Inspired Energy Storage Joint for Variable Jumping Trajectory Control.- Design and Control of a Novel Six-Legged Robot for Flat, Downhill, and Uphill Skiing .- Structure Design and Fall Trajectory Planning of an Electrically Driven Humanoid Robot.- HexGuide: A Hexapod Robot for Autonomous Blind Guidance in Challenging Environments.- Force-Estimation Based Interaction of Legged Robots through Whole-Body Dynamics.- Lightweight Design and Property Analysis of Humanoid Robot Thigh Integrated Structure With Appearance.- Joint Torque and Ground Reaction Force Estimation for a One-Legged Hopping Robot.- Predefined-Time External Force Estimation for Legged Robots.- Movement Analysis of a Landing Buffer Mobile Mechanism with Eccentric Load.- A Lightweight Manipulator Design for Quadruped Robots and Stable Locomotion Control with the Manipulator.- Recovery from Injury: Learning Bipedal Jumping Skills with a Motor Output Torque Limit Curriculum.- Recovery Planning for the Legged Mobile Lunar Lander.

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Book SynopsisThe 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023.The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows:Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application.Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot.Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots.Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots.Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots.Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics.Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction.Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms.Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.Table of Contents​Visual and Visual-tactile Perception for Robotics.- 6D Pose Estimation Method of Metal Parts for Robotic Grasping Based on Semantic-level Line Matching.- GelSplitter: Tactile Reconstruction from Near Infrared and Visible Images.- GelFlow: Self-Supervised Learning of Optical Flow for Vision-Based Tactile Sensor Displacement Measurement.- CLOE: Novelty Detection via Contrastive Learning with Outlier Exposure.- Detection and Positioning of Workpiece Grinding Area in Dark Scenes with Large Exposure.- Hardware-Free Event Cameras Temporal Synchronization Based on Event Density Alignment.-- A Structure-Responsive CNN-Based Approach for Loop Closure Detection in Appearance-Changing Environments.- Visual Sensor Layout Optimization of a Robotic Mobile Adhesive Removal System for Wind Turbine Blade Based on Simulation.- Perception, Interaction, and Control of Wearable Robots.- Kinematic and Static Analysis of Flexible Link Tensegrity Robots.- An Autoencoder-Based Feature Extraction Method Applied to the Detection of Lateral Walking Gait Phase.- Sparse Adaptive Channel Estimation Based on Multi-Kernel Correntropy.- Towards Intercontinental Teleoperation: A Cloud-Based Framework for Ultra-Remote Human-Robot Dual-Arm Motion Mapping.- A Lightweight Ankle Exoskeleton Driven by Series Elastic Actuator.- Simulation Analysis of Synchronous Walking Control for Centaur System.- Kinematics Analysis of the Wearable Waist Rehabilitation Robot.- 3D Human Pose Estimation in Video for Human-Computer/Robot Interaction.- A Real-time AGV Gesture Control Method Based on Body Part Detetcion.- Predict Hip Joint Moment Using CNN for Control.- Marine Robotics and Applications.- Study on design and performance of a bionic fish driven by four IPMC fins.- Optimization of Energy Storage for A Miniature Water Jumping Robot.- Design and Research of Flatworm-inspired Marine Exploration Robot.- Coordinated Passive Maneuvering Target Tracking by Multiple Underwater Vehicles Based on Asynchronous Sequential Filtering.- Robust Tube-Based Model Predictive Control for Marine Ship-mounted Cranes.- Multi-UUV/USV Adaptive Cooperative Search Using Online State Information.- Design and Analysis of Co-Axial Twin-Propeller Trans-Media Vehicle.- Design of an Autonomous Underwater Vehicle for Targeted Water Sampling.- A Novel Motion Planning Algorithm Based on RRT-Connect and Bidirectional Approach for Free-Floating Space Robot.- A Hybrid Workspace Mapping Method Based on Force Feedback for Underwater Teleoperation Systems.- A Lyapunov-based Model Predictive Virtual Vehicle Guidance for Path Following Control of Autonomous Marine Vehicles.- Overview of Technologies in Marine Robotics.- Multi-robot Systems for Real World Applications.- An MFG Online Path Planning Algorithm Based on Upper and Lower Structure.- Intelligent Scalable and Fault-tolerant Coordination Approach for Collective Construction Robots .- Performance Analysis and Configuration Optimization of a Hexapod Platform with Flexure Hinges.- Dynamic Modeling and Control of Winch-Integrated Cable-Driven Parallel Robots Using Singular Perturbation Method.- Multi-input Multi-output Sliding Mode Control with High Precision and Robustness for a 6-PSU Parallel Robot.- Efficient Trajectory Planning for Coordinated Arrival of Fixed-Wing UAV Swarm.- Spontaneous Emergence of Multitasking in Minimal Robotic Systems.- Cooperative Control of Dual-Manipulator System with Unknown Dynamic Parameters.- Disturbance Rejection Fixed Point Control of DELTA Parallel Manipulator Mounted on Autonomous Underwater Vehicle.- Efficient Autonomous Exploration of Unknown Environment using Regions Segmentation and VRP.- Modeling of the electromagnetic launching process for a tethered-net capturing system.- Neural Network-Based Formation Control of Autonomous Underwater Vehicles Under Disturbance in 3D Space.- Event-Triggered Model Predictive Mean-Field Control for Stabilizing Robotic Swarm.- Risk-Aware Motion Planning for Very-Large-Scale Robotics Systems Using Conditional Value-at-Risk.- Physical and Neurological Human-Robot Interaction.- An Adaptive Impedance Control Method for Human-Robot Interaction.- Design of a lower limb rehabilitation training robot based on a double four-bar synchronous motion mechanism.- Upper Limb Motion Rehabilitation Training Robot Based on A Spatial RRSS Rigid-Body Guidance Mechanism.- Mask R-CNN with attention mechanism for detection and segmentation.- Design and Variable Parameter Control Strategy of Weight Support Gait Training Robot.- CMM-based Cooperative Control Strategy of Supernumerary Robotic Limbs for Human Motion.

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Book SynopsisThe 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023.The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows:Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application.Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot.Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots.Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots.Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots.Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics.Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction.Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms.Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.Table of Contents​Innovative Design and Performance Evaluation of Robot Mechanisms - Ⅱ.- Design and Analysis of a Novel Ring Truss Deployable Antenna Mechanism.- Model-based Performance Enhancement for Compound Twisted and Coiled Actuators.- Lightweight design method of stacker column structure based on multi-parameter sensitivity analysis.- Optimum Design of 3-UPS/S Parallel Humanoid Wrist Joint.- Kinematic Analysis of Overrunning on a Swing Arm Tracked Mobile Chassis.- Design and Implementation of a Modular Self-reconfigurable Spherical Robot Connected by Magnetic Force.- Graph Synthesis of Generalized Parallel Mechanisms with Coupling Sub-Chains.- Analysis of Mechanism Elastodynamic Performance in Automatic Excavating Process of Excavating Robot.- Measurement and Analysis of End Jitter of Six-axis Industrial Robots.- Description of configuration transformation matrix of reconfigurable mechanism and automatic retrieval and recognition of motion mode.- Design of a voice coil motor-driven multi-DOF parallel micropositioning stage.- Structural Design of a Multi mode Variable Coupling Multi axis Parallel Mobile Robot.- Design and Kinematic Analysis of DNA Nanomachines.- Design and analysis of a new type of solar panel.- Cutting-edge Research in Robotics.- Real-Time Monitoring System of Spray-Painting Robot Based on Five-Dimension Digital Twin Model.- A Methodology for Optimization Design of Parallel Manipulators with Similar Stiffness Performance Design.- Collaborative Robot-Oriented Joint Real-time Control Based on Heterogeneous Embedded Platform.- A Novel Sensitivity Analysis Method for Geometric Errors of a Parallel Spindle Head.- A Novel Prognostic Method for Wear of Sliding Bearing based on SFENN.- Accurate Interpolation Algorithm Based on Fir Filters with Local Dynamic Adjustment.- Investigation of Soft Acoustic Waveguide Dispersion for Wearable Strain Sensing in Human Motion Monitoring.- Design and Optimization of Compliant Rotational Hinge Based on Curved Beam.- A Visual-Inertial Fusion Mapping and Localization System Using AprilTag in GNSS-Denied Scenes .- An Orientation Measurement Method for Industry Robot Based on Laser Tracker.- Programming the Motion of Nanofiber Mat Actuator Through an Area Selective Epoxy Coating Method.- Design of a Multi-Robot Digital Twin System with Bidirectional Motion Synchronization Capabilities.

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Book SynopsisThis book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.Table of ContentsChapter 1: Diagnosis of Parkinson disease using Ensemble methods for Class Imbalance Problem.- Chapter 2: A Comparative Analysis of Pneumonia Detection Using Chest X-Rays With DNN.- Chapter 3: Machine Learning Based Binary Sentiment Classification of Movie Reviews in Hindi (Devanagari Script).- Chapter 4: Deep Learning-Based Recommendation Systems: Review and Critical Analysis.- Chapter 5: Retention in Second Year Computing Students in a London-Based University During The Post-Covid-19 Era Using Learned Optimism as a Lens: A Statistical Analysis in R.- Chapter 6: Alzheimer’s Disease Knowledge Graph Based on Ontology and Neo4j Graph Database.- Chapter 7: Forecasting Bitcoin Prices in the Context of the COVID19 Pandemic Using Machine Learning Approaches.- Chapter 8: Online Food Delivery Customer Churn Prediction: A Quantitative Analysis on the Performance of Machine Learning Classifiers.- Chapter 9: Prevention Equipment for COVID-19 Spread Using IoT and Multimedia-Based Solutions.- Chapter 10: Renal Disease Classification using Image Processing. etc.

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Book SynopsisThis book constitutes the refereed proceedings of the 12th International Conference on Health Information Science, HIS 2023, held in Melbourne, VIC, Australia, during October 23–24, 2023.The 20 full papers and 9 short papers included in this book were carefully reviewed and selected from 54 submissions. They were organized in topical sections as follows: Depression & Mental Health, Data Security, Privacy & Healthcare Systems, Neurological & Cognitive Disease Studies, COVID-19 Impact Studies, Advanced Medical Data & AI Techniques, Predictive Analysis & Disease Recognition, Medical Imaging & Dataset Exploration, Elderly Care and Knowledge Systems.Table of ContentsDepression & Mental Health.- Detection of depression and its likelihood in children and adolescents: Evidence from a 15-years study.- A combined attribute extraction method for detecting Postpartum Depression using Social Media.- Network Analysis of Relationships and Change Patterns in Depression and Multiple Chronic Diseases based on the China Health and Retirement Longitudinal Study.- Exploring Etiology of Nonsuicidal Self-Injury by Using Knowledge Graph Approach.- A Question and Answering System for Mental Health of the ElderlyBased on BiLSTM-CRF Model and Knowledge Graph.- Data Security, Privacy & Healthcare Systems.- Australia's Notifiable Data Breach scheme: An analysis of risk management findings for healthcare.- Analysis and Protection of Public Medical Dataset: from Privacy Perspective.- Enhancing Health Information Systems Security: An Ontology Model Approach.- Developing a Risk Management Framework for E-health Care Delivery.- Neurological & Cognitive Disease Studies.- Knowledge-Based Nonlinear to Linear Dataset Transformation for Chronic Illness Classification.- A Robust Approach for Parkinson Disease Detection from Voice Signal.- Analysis on Association between Vascular Risk Factors and Lifestyle Factors with the risk of Dementia/Alzheimer's Disease using Medical Ontologies.- COVID-19 Impact Studies.- Unveiling the Pandemic's Impact: A Dataset for Probing COVID-19's Effects on E-Learning Activities and Academic Performance.- Understanding the influence of multiple factors on the spread of Omicron variant strains via the Multivariate Regression Method.- Analyzing the Impact of COVID-19 on Education: A Comparative Study Based on TOEFL Test Results.- Advanced Medical Data & AI Techniques.- BiblioEngine: An AI-empowered Platform for Disease Genetic Knowledge Mining.- Enhancing Clustering Performance in Sepsis Time Series Data Using Gravity Field.- Multi-modal Medical Data Exploration Based on Data Lake.- Multi-model Transfer Learning and Genotypic Analysis for Seizure Type Classification.- Requirement survey in Thai clinician for designing digital solution of pain assessment.- Predictive Analysis & Disease Recognition.- A Comprehensive Approach for Enhancing Motor Imagery EEG Classification in BCI's.- Image Recognition of Chicken Diseases Based on Improved Residual Networks.- An Adaptive Feature Fusion Network for Alzheimer's Disease Prediction.- A Review on Predicting Drug Target Interactions Based on Machine Learning.- KNN-Based Patient Network and Ensemble Machine Learning for Disease Prediction.- Medical Imaging & Dataset Exploration.- Optimizing the Size of Peritumoral Region for Assessing Non-Small Cell Lung Cancer Heterogeneity Using Radiomics.- Multi-dimensional Complex Query Optimization for Disease-specific Data Exploration Based on Data Lake.- Analyzing Health Risks Resulting from Unplanned Land Use Plan and Structure: A Case Study in Historic Old Dhaka.- Elderly Care & Knowledge Systems.- Home Self-medication Question-Answering System for the Elderly Based on Seq2Seq Model and Knowledge Graph Technology.- Constructing Multi-Constrained Cognitive Diagnostic Test: An Improved Ant Colony Optimization Algorithm.- Enhancing Patient Safety in Pharmacotherapy.

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Book SynopsisThe book is a comprehensive guide that explores the concept of data economy and its implications in today's world. The book discusses the principles and components of the ecosystem, the challenges and opportunities presented by data monetization, and the potential risks related to data privacy. Real-life examples and case studies are included to understand the concepts better. The book is suitable for individuals in data science, economics, business, and technology and for students, academics, and policymakers. It is an excellent read for anyone interested in the data economy.Table of ContentsChapter 1: Data Economy.- Chapter 2: Navigating the Data Deluge: Challenges and Opportunities.- Chapter 3: Data Monetization.- Chapter 4: Demographic Trend of Data Economy.- Chapter 5: The Economy of Data Privacy.- Chapter 6: Application of Data Economy.

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Book SynopsisThis book constitutes the refereed proceedings of the 19th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2023, held in conjunction with the 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2023), in November 2023, in Jakarta, Indonesia. The 9 full papers and 2 short papers included in this volume were carefully reviewed and selected from 28 initial submissions. They are organized in the topical section such as machine learning, natural language processing, and intelligent systems.Table of ContentsPredicting Peak Demand Days for Asthma-Related Emergency Hospitalisations: A Machine Learning Approach.- Discovering Maximal High Utility Co-location Patterns from Spatial Data.- Exploring the Potential of Image Overlay in Self-Supervised Learning: A Study on SimSiam Networks and Strategies for Preventing Model Collapse.- BoCB: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain.- Automated Cattle Behavior Classification Using Wearable Sensors and Machine Learning Approach.- LexiFusedNet: A Unified Approach for Imbalanced Short-text Classification using Lexicon-based Feature Extraction, Transfer Learning and One Class Classifiers.- Information Gerrymandering in Elections.- An Assessment of the Influence of Interaction and Recommendation Approaches on the Formation of Information Filter Bubbles.- Blockchain as a Collaborative Technology - Case Studies in the Real Estate Sector in Vietnam.- Indonesian Forest Fire Data Clustering using Spatiotemporal Data Using Grid Density-Based Clustering Algorithm.

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsLearning Bottleneck Transformer for Event Image-Voxel Feature Fusion based Classification.- Multi-scale Dilated Attention Graph Convolutional Network for Skeleton-Based Action Recognition.- Auto-Learning-GCN: An Ingenious Framework for Skeleton-based Action Recognition.- Skeleton-based Action Recognition with Combined Part-wise Topology Graph Convolutional Networks.- Segmenting Key Clues to Induce Human-Object Interaction Detection.- Lightweight Multispectral Skeleton and Multi-Stream Graph Attention Networks for Enhanced Action Prediction with Multiple Modalities.- Spatio-temporal Self-supervision for Few-shot Action Recognition.- A Fuzzy Error based Fine-tune Method for Spatio-temporal Recognition Model.- Temporal-Channel Topology Enhanced Network for Skeleton-Based Action Recognition.- HFGCN-Based Action Recognition System for Figure Skating.- Image Priors Assisted Pre-training for Point Cloud Shape Analysis.-AMM-GAN: Attribute-Matching Memory for Person Text-to-Image Generation.- RecFormer: Recurrent Multi-modal Transformer with History-aware Contrastive Learning for Visual Dialog.- KV Inversion: KV Embeddings Learning for Text-Conditioned Real Image Action Editing.- Enhancing Text-Image Person Retrieval through Nuances Varied Sample.- Unsupervised Prototype Adapter for Vision-Language Models.- Multimodal Causal Relations Enhanced CLIP for Image-to-Text Retrieval.- Exploring Cross-Modal Inconsistency in Entities and Emotions for Multimodal Fake News Detection.- Deep Consistency Preserving Network for Unsupervised Cross-modal Hashing.- Learning Adapters for Text-guided Portrait Stylization with Pretrained Diffusion Models.- EdgeFusion: Infrared and Visible Image Fusion Algorithm in Low Light.- An Efficient Momentum Framework for Face-Voice Association Learning.- Multi-modal Instance Refinement for Cross-domain Action Recognition.- Modality Interference Decoupling and Representation Alignment for Caricature-Visual Face Recognition.- Plugging Stylized Controls in Open-Stylized Image Captioning.- MGT: Modality-Guided Transformer for Infrared and Visible Image Fusion.- Multimodal Rumor Detection by Using Additive Angular Margin with Class-aware Attention for Hard Samples.- An Effective Dynamic Reweighting Method for Unbiased Scene Graph Generation.- Multi-modal Graph and Sequence Fusion Learning for Recommendation.- Co-attention guided local-global feature fusion for aspect-level multimodal sentiment analysis.- Discovering Multimodal Hierarchical Structures with Graph Neural Networks for Multi-modal and Multi-hop Question Answering.- Enhancing Recommender System with Multi-modal Knowledge Graph.- Location Attention Knowledge Embedding Model for Image-Text Matching.- Pedestrian Attribute Recognition Based on Multimodal Transformer.- RGB-D Road Segmentation Based on Geometric Prior Information.- Contrastive Perturbation Network for Weakly Supervised Temporal Sentence Grounding.- MLDF-Net: Metadata Based Multi-level Dynamic Fusion Network.- Efficient Adversarial Training with Membership Inference Resistance.- Enhancing Image Comprehension for Computer Science Visual Question Answering.- Cross-Modal Attentive Recalibration and Dynamic Fusion for Multispectral Pedestrian Detection.

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsDeep Stereo Matching with Superpixel-based Feature and Cost Aggregation.- GMA3D: Local-Global Attention Learning to Estimate Occluded Motions of Scene Flow.- Diffusion-based 3D Object Detection with Random Boxes.- Blendshape-based Migratable Speech-driven 3D Facial Animation with Overlapping Chunking-Transformer.- FIRE: Fine Implicit Reconstruction Enhancement with Detailed Body Part Labels and Geometric Features.- Sem-Avatar: Semantic Controlled Neural Field for High-Fidelity Audio Driven Avatar.- Depth optimization for accurate 3D Reconstruction from light field images.- TriAxial Low-Rank Transformer for Efficient Medical Image Segmentation.- SACFormer: Unify Depth Estimation and Completion with Prompt.- Rotation-Invariant Completion Network.- Towards Balanced RGB-TSDF Fusion for Consistent Semantic Scene Completion by 3D RGB Feature Completion and a Classwise Entropy Loss Function.- FPTNet: Full Point Transformer Network for Point Cloud Completion.- Efficient Point-based Single Scale 3D Obiect Detection from Traffic Scenes.- Matching-to-Detecting: Establishing Dense and Reliable Correspondences between Images.- Solving Generalized Pose Problem of Central and Non-central Cameras.- RICH: Robust Implicit Clothed Humans Reconstruction from Multi-Scale Spatial Cues.- An Efficient and Consistent Solution to the PnP Problem.- Autoencoder and Masked Image Encoding-based Attentional Pose Network.- A Voxel-Based Multiview Point Cloud Refinement Method via Factor Graph Optimization.- SwinFusion: channel query-response based feature fusion for monocular depth estimation.- PCRT: Multi-branch Point Cloud Reconstruction from a Single Image with Transformers.- Progressive Point Cloud Generating by Shape Decomposing and Upsampling.- Three-dimensional Plant Reconstruction with Enhanced Cascade-MVSNet.- Learning Key Features Transformer Network for Point Cloud Processing.- Unsupervised Domain Adaptation for 3D Object Detection via Self-Training.- Generalizable Neural Radiance Field with Hierarchical Geometry Constraint.- ACFNeRF: Accelerating and Cache-Free Neural Rendering via Point Cloud-based Distance Fields.- OctPCGC-Net: Learning Octree-Structured Context Entropy Model for Point Cloud Geometry Compression.- Multi-modal Feature Guided Detailed 3D Face Reconstruction from a Single Image.- Advanced License Plate Detector in Low-Quality Images with Smooth Regression Constraint.- A Feature Refinement Patch Embedding-Based Recognition Method for Printed Tibetan Cursive Script.- End-to-End Optical Music Recognition with Attention Mechanism and Memory Units Optimization.- Tripartite Architecture License Plate Recognition based on Transformer.- Focus the Overlapping Problem on Few-Shot Object Detection via Multiple Predictions.- Target-aware Bi-Transformer for Few-Shot Segmentation.- Convex Hull Collaborative Representation Learning on Grassmann Manifold with L_1 norm Regularization.- FUFusion: Fuzzy Sets Theory for Infrared and Visible Image Fusion.-Progressive Frequency-aware Network for Laparoscopic Image Desmoking.-A pixel-level segmentation method for water surface reflection detection

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsLoss Filtering Factor for Crowd Counting.- Classifier Decoupled Training for Black-Box Unsupervised Domain Adaptation.- Unsupervised Concept Drift Detection via Imbalanced Cluster Discriminator Learning.- Unsupervised Domain Adaptation for Optical Flow Estimation.- Continuous Exploration via Multiple Perspectives in Sparse Reward Environment.- Network Transplanting for the Functionally Modular Architecture.- TiAM-GAN: Titanium Alloy Microstructure Image Generation Network.- A Robust Detection and Correction Framework for GNN-based Vertical Federated Learning.- QEA-Net: Quantum-Effects-based Attention Networks.- Learning Scene Graph for Better Cross-Domain Image Captioning.- Enhancing Rule Learning on Knowledge Graphs through Joint Ontology and Instance Guidance.- Explore Across-Dimensional Feature Correlations for Few-Shot Learning.- Pairwise-emotion Data Distribution Smoothing for Emotion Recognition.- SIEFusion: Infrared and Visible Image Fusion via Semantic Information Enhancement.- DeepChrom: A Diffusion-Based Framework for Long-Tailed Chromatin State Prediction.- Adaptable Conservative Q-Learning for Offline Reinforcement Learning.- Boosting Out-of-Distribution Detection with Sample Weighting.- Causal discovery via the subsample based reward and punishment mechanism.- Local Neighbor Propagation Embedding.- Inter-class sparsity based non-negative transition sub-space learning.- Incremental Learning Based on Dual-branch Network.- Inter-Image Discrepancy Knowledge Distillation for Semantic Segmentation.- Cascaded Bilinear Mapping Collaborative Hybrid Attention Modality Fusion Model.- CasFormer: Cascaded Transformer based on Dynamic Voxel Pyramid for 3D Object Detection from Point Clouds.- Generalizable and Accurate 6D Object Pose Estimation Network.- An Internal-external Constrained Distillation Framework for Continual Semantic Segmentation.- MTD: Multi-Timestep Detector for Delayed Streaming Perception.- Semi-Direct SLAM with Manhattan for Indoor Low-texture Environment.- L2T-BEV: Local Lane Topology Prediction from Onboard Surround-View Cameras in Bird’s Eye View Perspective.- CCLane: Concise Curve Anchor-based Lane Detection Model with MLP-Mixer.- Uncertainty-aware Boundary Attention Network for Real-time Semantic Segmentation.- URFormer: Unified Representation LiDAR-Camera 3D Object Detection with Transformer.- A Single-Stage 3D Object Detection Method Based on Sparse Attention Mechanism.- WaRoNav: Warehouse Robot Navigation Based on Multi-View Visual-Inertial Fusion.- Enhancing Lidar and Radar Fusion for Vehicle Detection in Adverse Weather via Cross-Modality Semantic Consistency.- Enhancing Active Visual Tracking under Distractor Environments.- Cross-modal and Cross-domain Knowledge Transfer for Label-free 3D Segmentation.- Cross-task Physical Adversarial Attack against Lane Detection System Based on LED Illumination Modulation.- RECO: Rotation Equivariant COnvolutional Neural Network for Human Trajectory Forecasting.- FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and AnalysisTable of ContentsShared Nearest Neighbor Calibration For Few-Shot Classification.- Prototype Rectification with Region-Wise Foreground Enhancement for Few-Shot Classification.- Rotation Augmented Distillation for Exemplar-Free Class Incremental Learning with Detailed Analysis.- Nonconvex Tensor Hypergraph Learning for Multi-view Subspace Clustering.- A Novel Method for Identifying Bipolar Disorder based on Diagnostic Texts.- Deep Depression Detection based on Feature Fusion and Result Fusion.- Adaptive Cluster Assignment for Unsupervised Semantic Segmentation.- Confidence-Guided Open-World Semi-Supervised Learning.- SSCL: Semi-supervised Contrastive Learning for Industrial Anomaly Detection.- One Step Large-scale Multi-view Subspace Clustering based on Orthogonal Matrix Factorization with Consensus Graph Learning.- Deep Multi-Task Image Clustering with Attention-guided Patch Filtering and Correlation Mining.- Deep Structure and Attention Aware Subspace Clustering.- Broaden Your Positives: A General Rectification Approach for Novel Class Discovery.- CE2: A Copula Entropic Mutual Information Estimator for Enhancing Adversarial Robustness.- Two-step projection of sparse discrimination between classes for unsupervised domain adaptation.- Enhancing Adversarial Robustness via Stochastic Robust Framework.- Pseudo Labels Refinement with Stable Cluster Reconstruction for Unsupervised Re Identification.- Ranking Variance Reduced Ensemble Attack with Dual Optimization Surrogate Search.- PCR: A Large-Scale Benchmark for Pig Counting in Real World.- A Hierarchical Theme Recognition Model for Sandplay Therapy.- Change-Aware Network for Damaged Roads Recognition and Assessment Based on Multi-temporal Remote Sensing Imageries.- UAM-Net: An Attention-Based Multi-Level Feature Fusion UNet for Remote Sensing Image Segmentation.- Improved Conditional Generative Adversarial Networks for SAR-to-Optical Image Translation.- A Novel Cross Frequency-domain Interaction Learning for Aerial Oriented Object Detection.- DBDAN: Dual-Branch Dynamic Attention Network for Semantic Segmentation of Remote Sensing Images.- Multi-scale Contrastive Learning for Building Change Detection in Remote Sensing ImagesShadow Detection of Remote Sensing Image by Fusion of Involution and Shunted Transformer.- Few-shot Infrared Image Classification with Partial Concept Feature.- AGST-LSTM: The ConvLSTM model combines attention and gate structure for spatiotemporal sequence prediction learning.- A Shape-based Quadrangle Detector for Aerial Images.- End-to-end Unsupervised Style and Resolution Transfer Adaptation Segmentation Model for Remote Sensing ImagesA physically feasible counter-attack method for remote sensing imaging point clouds.- Adversarial Robustness via Multi-experts framework for SAR recognition with Class Imbalanced.- Recognizer Embedding Diffusion Generation for Few-shot SAR Recognization.- A Two-Stage Federated Learning Framework for Class Imbalance in Aerial Scene ClassificationSAR Image Authentic Assessment with Bayesian Deep Learning and Counterfactual Explanations.- Circle Representation Network for Specific Target Detection in Remote Sensing Image.- A Transformer-Based Adaptive Semantic Aggregation Method for UAV Visual Geo-Localization.- Lightweight Multiview Mask Contrastive Network for Small-sample Hyperspectral Image Classification.- Dim moving target detection based on imaging uncertainty analysis and hybrid entropy

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsFeature Enhancement with Text-specific Region Contrast for Scene Text Detection.- Learning Efficient Representations for Patent Drawing Retrieval.- HelixNet: Dual Helix Cooperative Decoders for Scene Text Removal.- Semantic-information Space Sharing Interaction Network for Arbitrary Shape Text Detection.- AIE-KB: Information Extraction Technology with Knowledge Base for Chinese Archival Scenario.- Deep Hough Transform For Gaussian Semantic Box-Lines Alignment.- Chinese-Vietnamese Cross-lingual Event Causality Identification Based on Syntactic Graph Convolution.- MCKIE: Multi-Class Key Information Extraction from Complex Documents based on Graph Convolutional Network.- A Pre-trained Model For Chinese Medical Record Punctuation Restoration.- "English and Spanish Bilinguals’ Language Processing: An ALE-based Meta-analysis of Neuroimaging Studies".- Robust Subspace Learning with Double Graph Embedding Unsupervised Feature Selection via Nonlinear Representation and Adaptive Structure Preservation.- Text Causal Discovery Based on Sequence Structure Information.- MetaSelection: A Learnable Masked AutoEncoder for Multimodal Sentiment Feature Selection.- Image Manipulation Localization based on Multiscale Convolutional Attention.- Bi-Stream Multiscale Hamhead Networks with Contrastive Learning for Image forgery Localization.- Fuse Tune: Hierarchical Decoder Towards Efficient Transfer Learning.- Industrial-SAM with Interactive Adapter.- Mining Temporal Inconsistency with 3D Face Model for Deepfake Video Detection.- DT-TransUNet: A Dual-task Model for Deepfake Detection and Segmentation.- Camouflaged Object Detection via Global-edge Context and Mixed-scale Refinement.- Enhancing CLIP-Based Text-Person Retrieval by Leveraging Negative Samples.- Global Selection and Local Attention Network for Referring Image Segmentation.- MTQ-Caps: A Multi-Task Capsule Network for Blind Image Quality Assessment.- VCD: Visual Causality Discovery for Cross-Modal Question Reasoning.- Multimodal Topic and Sentiment Recognition for Chinese Data Based on Pre-trained Encoders.- Multi-Feature Fusion-Based Central Similarity Deep Supervised Hashing.- VVA: Video Values Analysis.- Dynamic Multi-modal Prompting for Efficient Visual Grounding.- A Graph-involved Lightweight Semantic Segmentation Network.- User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning.- An End-to-End Transformer with Progressive Tri-modal Attention for Multi-modal Emotion Recognition.- Target-oriented Multi-criteria Band Selection for Hyperspectral Image.- Pairwise Negative Sample Mining for Human-Object Interaction Detection.- An Evolutionary Multiobjective Optimization Algorithm based on Manifold Learning.- Path Planning of Automatic Parking System by A Point-based Genetic AlgorithmPenalty-Aware Memory Loss for Deep Metric Learning.- Central and Directional Muti-Neck Knowledge Distillation.- Online Class-incremental Learning in Image Classification based on AttentionOnline airline baggage packing based on hierarchical tree A2C-reinforcement learning framework

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsA Quantum-based Attention Mechanism in Scene Text Detection.- NCMatch: Semi-Supervised Learning with Noisy Labels via Noisy Sample Filter and Contrastive Learning.- Data-free Low-bit Quantization via Dynamic Multi-teacher Knowledge Distillation.- LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation.- DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation.- Space-Transform Margin Loss with Mixup for Long-tailed Visual Recognition.- A Multi-Perspective Squeeze Excitation Classifier Based on Vision Transformer for Few Shot Image Classification.- ITCNN: Incremental Learning Network Based on ITDA and Tree Hierarchical CNN.- Periodic-Aware Network for Fine-grained Action Recognition.- Learning Domain-invariant Representations from Text for Domain Generalization.- TSTD:A Cross-modal Two Stages Network with New Trans-Decoder for Point Cloud Semantic Segmentation.- NeuralMAE: Data-Efficient Neural Architecture Predictor with Masked Autoencoder.- Co-Regularized Facial Age Estimation with Graph-Causal Learning.- Online Distillation and Preferences Fusion for Graph Convolutional Network-based Sequential Recommendation.- Grassmann Graph Embedding for Few-Shot Class Incremental Learning.- Global Variational Convolution Network for Semi-Supervised Node Classification on Large-scale Graphs.- Frequency Domain Distillation for Data-Free Quantization of Vision Transformer.- An ANN-Guided Approach to Task-Free Continual Learning with Spiking Neural Networks.- Multi-Adversarial Adaptive Transformers for Joint Multi-Agent Trajectory Prediction.- Enhancing Open-Set Object Detection via Uncertainty-Boxes Identification.- Interventional Supervised Learning for Person Re-Identification.- DP-INNet: Dual-Path Implicit Neural Network for Spatial and Spectral Features Fusion in Pan-sharpening.- Stable Visual Pattern Mining via Pattern Probability Distribution.- Dynamic Visual Prompt Tuning for Parameter Efficient Transfer Learning.- C-volution: A Hybrid operator for Visual Recognition.- Motor Imagery EEG Recognition Based on an Improved Convolutional Neural Network with Parallel Gate Recurrent Unit.- A Stable Vision Transformer for Out-of-Distribution Generalization.- Few-Shot Classification with Semantic Augmented Activators.- MixPose: 3D Human Pose Estimation with Mixed Encoder.- Image Manipulation Detection Based on Ringed Residual Edge Artifact Enhancement and Multiple Attention Mechanisms.- Improving Masked Autoencoders by Learning Where to Mask.- An Audio Correlation-Based Graph Neural Network for Depression Recognition.- Dynamic Gesture Recognition based on 3D Central Difference Separable Residual LSTM Coordinate Attention Networks.- QESAR: Query Effective Decision-based Attack on Skeletal Action Recognition.- A Closer Look at Few-shot Object Detection.- Learning-without-Forgetting via Memory Index in Incremental Object Detection.- SAMDConv: Spatially Adaptive Multi-scale Dilated Convolution.- SADD:Generative Adversarial Networks via Self-Attention and Dual Discriminator in Unsupervised Domain Adaptation.- ELFLN: An Efficient Lightweight Facial Landmark Network Based on Hybrid Knowledge Distillation.- Enhancing Continual Noisy Label Learning with Uncertainty-based Sample Selection and Feature Enhancement

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsDecoupled Contrastive Learning for Long-Tailed Distribution.- MFNet: A Channel Segmentation-based Hierarchical Network for Multi-Food Recognition.- Improving the Adversarial Robustness of Object Detection with Contrastive Learning.- CAWNet: A Channel Attention Watermarking Attack Network Based on CWABlock.- Global Consistency Enhancement Network for Weakly-Supervised Semantic Segmentation.- Enhancing Model Robustness against Adversarial Attacks with an Anti-Adversarial Module.- FGPTQ-ViT:Fine-grained Post-training Quantization for Vision Transformers.- Learning Hierarchical Representations in Temporal and Frequency Domains for Time Series Forecasting.- DeCAB: Debiased Semi-Supervised Learning for Imbalanced Open-Set Data.- An Effective Visible-Infrared Person Re-identification Network based on Second-Order Attention and Mixed Intermediate Modality.- Quadratic polynomial residual network for no-reference image quality assessment.- Interactive Learning for Interpretable Visual Recognition via Semantic-Aware Self-Teaching Framework.-Adaptive and Compact Graph Convolutional Network for Micro-Expression Recognition.- Consistency Guided Multiview Hypergraph Embedding Learning with Multiatlas-Based Functional Connectivity Networks Using Resting-State fMRI.- A Diffusion Simulation User Behavior Perception Attention Network for Information Diffusion Prediction.- A Representation Learning Link Prediction Approach Using Line Graph Neural Networks.- Event Sparse Net: Sparse Dynamic Graph Multi-representation Learning with Temporal Attention for Event-based Data.- Federated Learning Based on Diffusion Model to Cope with non-IID DataSFRSwin: A shallow significant feature retention Swin Transformer for fine-grained image classification of wildlife species.- A robust and high accurate method for hand kinematics decoding from neural populations.- Multi-head Attention Induced Dynamic Hypergraph Convolutional Networks.- Self Supervised Temporal Ultrasound Reconstruction for Muscle Atrophy EvaluationSalient Object Detection Using Reciprocal Learning.- Graphormer-based Contextual Reasoning Network for Small Object Detection.- PVT-Crowd:Bridging Multi-scale Features from Pyramid Vision Transformer for Weakly-Supervised Crowd Counting.- Multi-view Contrastive Learning Network for Recommendation.- Uncertainty-confidence fused pseudo-labeling for Graph Neural Networks.- FSCD-Net: A Few-Shot Stego Cross-Domain Net for Image Steganalysis.- Preference Contrastive Learning for Personalized Recommendation.- GLViG: Global and Local Vision GNN May be What You Need for Vision.- SVDML: Semantic and Visual space Deep Mutual Learning for Zero-Shot Learning.- Heterogeneous Graph Attribute Completion via Efficient Meta-path Context-aware Learning.- Fine-Grain Classification Method of Non-Small Cell Lung Cancer Based on Progressive Jigsaw and Graph Convolutional Network.- Improving Transferability of Adversarial Attacks with Gaussian Gradient Enhance Momentum.- Boundary Guided Feature fusion Network for Camouflaged Object Detection.- Saliency Driven Monocular Depth Estimation based on Multi-scale Graph Convolutional Network.- Mask-guided Joint Single Image Specular Highlight Detection and Removal.- CATrack: Convolution and Attention Feature Fusion for Visual Object TrackingSText-DETR: End-to-End Arbitrary-Shaped Text Detection with Scalable Query in Transformer.- SSHRF-GAN: Spatial-Spectral Joint High Receptive Field GAN for Old Photo Restoration

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsDual-stream Context-aware Neural Network for Survival Prediction from Whole Slide Images.- A multi-label image recognition algorithm based on spatial and semantic correlation interaction.- Hierarchical Spatial-Temporal Network for Skeleton-Based Temporal Action Segmentation.- Multi-Behavior Enhanced Graph Neural Networks for Social Recommendation.- A Complex-valued Neural Network based Robust Image Compression.- Binarizing Super-resolution Neural Network without Batch Normalization.- Infrared and Visible Image Fusion via Test-Time Training.- Graph-based Dependency-aware Non-Intrusive Load Monitoring.- Few-shot Object Detection via Classify-free RPN.- IPFR: Identity-Preserving Face Reenactment with Enhanced Domain Adversarial Training and Multi-level Identity Priors.- L2MNet: Enhancing Continual Semantic Segmentation with Mask Matching.- Adaptive Channel Pruning for Trainability Protection.- Exploiting Adaptive Crop and Deformable Convolution for Road Damage Detection.- Cascaded-scoring Tracklet Matching for Multi-object Tracking.- Boosting Generalization Performance in Person Re-IdentificationSelf-Guided Transformer for Video Super-Resolution.- SAMP: Sub-task Aware Model Pruning with Layer-wise Channel Balancing for Person Search.- MKB: Multi-kernel Bures Metric for Nighttime Aerial Tracking.- Deep Arbitrary-Scale Unfolding Network for Color-Guided Depth Map Super-Resolution.- SSDD-Net: A Lightweight and Efficient Deep Learning Model for Steel Surface Defect Detection.- Effective Small Ship Detection with Enhanced-YOLOv7.- PiDiNeXt: An Efficient Edge Detector based on Parallel Pixel Difference Networks.- Transpose and Mask: Simple and Effective Logit-Based Knowledge Distillation for Multi-Attribute and Multi-Label Classification.- CCSR-Net: Unfolding coupled convolutional sparse representation for multi-focus image fusion.- FASONet: A Feature Alignment-Based SAR and Optical Image Fusion Network for Land Use Classification.- De Novo Design of Target-Specific Ligands Using BERT-Pretrained Transformer.- CLIP for Lightweight Semantic Segmentation.- Teacher-Student Cross-Domain Object Detection Model Combining Style Transfer and Adversarial Learning.- Computing 2D Skeleton via Generalized Electric Potential.- Illumination Insensitive Monocular Depth Estimation based on Scene Object Attention and Depth Map Fusion.- A Few-Shot Medical Image Segmentation Network with Boundary Category Correction.- Repdistiller: Knowledge Distillation Scaled by Re-parameterization for Crowd Counting.- Multi-depth Fusion Transformer and Batch Piecewise Loss for Visual Sentiment Analysis.- Expanding the Horizons: Exploring Further Steps in Open-Vocabulary Segmentation.- Exploring a Distillation with Embedded Prompts for Object Detection in Adverse Environments.- TEFNet: Target-Aware Enhanced Fusion Network for RGB-T Tracking.- DARN: Crowd Counting Network Guided by Double Attention Refinement.- DFR-ECAPA: Diffusion Feature Refinement for Speaker Verification based on ECAPA-TDNN.- Half Aggregation Transformer for Exposure Correction.- Deformable Spatial-Temporal Attention for Lightweight Video Super-Resolution

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsOKGR: Occluded Keypoint Generation and Refinement for 3D Object Detection.- Camouflaged Object Segmentation Based on Fractional Edge Perception.- DecTrans: Person Re-identification with Multifaceted Part Features via Decomposed Transformer.- AHT: A Novel Aggregation Hyper-Transformer for Few-Shot Object Detection.- Feature Refinement from Multiple Perspectives for High Performance Salient Object Detection.- Feature Disentanglement and Adaptive Fusion for Improving Multi-Modal Tracking.- Modality Balancing Mechanism for RGB-Infrared Object Detection in Aerial Image.- Pacific Oyster Gonad Identification and Grayscale Calculation Based on Unapparent Object Detection.- Multi-task Self-supervised Few-Shot Detection.- CSTrack: A Comprehensive and Concise Vision Transformer Tracker.- Feature Implicit Enhancement via Super-Resolution for Small Object Detection.- Improved detection method for SODL-YOLOv7 intensive juvenile abalone.- MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation.- Context-FPN and Memory Contrastive Learning for Partially Supervised Instance Segmentation.- A Dynamic Tracking Framework Based on Scene Perception.- HPAN: A Hybrid Pose Attention Network for Person Re-identification.- SpectralTracker: Jointly High and Low-Frequency Modeling for Tracking.- DiffusionTracker: Targets Denoising based on Diffusion Model for Visual Tracking.- Instance-proxy Loss for Semi-supervised Learning with Coarse Labels.- FAFVTC: A Real-time Network for Vehicle Tracking and Counting.- Ped-Mix: Mix Pedestrians for Occluded Person Re-Identification.- Object-Aware Transfer-based Black-box Adversarial Attack on Object Detector.- HTNet: A Hybrid Model Boosted by Triple Self-Attention for Crowd Counting.- Reliable Boundary Samples-based Proxy Pairs for Unsupervised Person Re- dentification.- High-Resolution Feature Representation Driven Infrared Small-Dim Object Detection.- Few-Shot Object Detection Algorithm Based on Adaptive Relation Distillation.- A real-time safety detector based on re-parameterization multiscale feature fusion for forklift driving.- RTMDet-R2：An Improved Real-Time Rotated Object Detector.- Boosting Object Detection in Foggy Scenes via Dark Channel Map and Union Training Strategy.- Object Centric Body Part Attention Network for Human-Object Interaction Detection.- Salient Feature Enhanced Multi-Object Tracking with Soft-Sparse Attention in Transformer.- A BiGRU based Adaptive Gain Estimation for radar Multi-target Tracking.- Prompt based Lifelong Person Re-identification.- Hierarchical Focused Feature Pyramid Network for Small Object Detection JLInst: Boundary-Mask Joint Learning for Instance Segmentation.- Boosting One-stage Multi Object Tracking with Attention Learning.- TPNet: Enhancing Weakly Supervised Polyp Frame Detection with Temporal Encoder and Prototype-based Memory Bank.- Learning Frequency-based Disentanglement and Filtering for Generalizable Person Re-identification.- Stereo3DMOT: Stereo Vision Based 3D Multi-Object Tracking with Multimodal ReID.- Emphasizing Boundary-Positioning and Leveraging Multi-Scale Feature Fusion for Camouflaged Object Detection

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsGrowth Simulation Network for Polyp Segmentation.- Brain Diffuser: An End-To-End Brain Image to Brain Network Pipeline.- CCJ-SLC: A Skin Lesion Image Classification Method based on Contrastive Clustering and Jigsaw Puzzle.- A Real-Time Network for Fast Breast Lesion Detection in Ultrasound Videos.- CBAV-Loss: Crossover and Branch Losses for Artery-vein Segmentation in OCTA Images.- Leveraging Data Correlations For Skin Lesion Classification.- CheXNet: Combing Transformer and CNN for Thorax Disease Diagnosis from Chest X-ray Images.- Cross Attention Multi Scale CNN-Transofmer Hybrid encoder is General Medical Image Learner.- Weakly/Semi-supervised Left Ventricle Segmentation in 2D Echocardiography with Uncertain Region-aware Contrastive Learning.- Spatial-Temporal Graph Convolutional Network for Insomnia Classification via Brain Functional Connectivity Imaging of rs-fMRI.- Probability-based Nuclei Detection and Critical-Region Guided Instance Segmentation.- FlashViT: A Flash Vision Transformer with Large-scale Token Merging for Congenital Heart Disease Detection.- Semi-supervised Retinal Vessel Segmentation through Point Consistency.- Knowledge Distillation of Attention and Residual U-Net: Transfer from Deep to Shallow Models for Medical Image Classification.- Two-stage deep learning segmentation for tiny brain regions.- Encoder Activation Diffusion and Decoder Transformer Fusion Network for Medical Image Segmentation.- Liver segmentation via learning cross-modality content-aware representation.- Semi-Supervised Medical Image Segmentation based on Multi-scale Knowledge Discovery and Multi-task Ensemble.- LATrans-Unet: Improving CNN-Transformer with Location-Adaptive for Medical Image Segmentation.- Adversarial Keyword Extraction and Semantic-Spatial Feature Aggregation for Clinical Report Guided Thyroid Nodule Segmentation.- A Multi-Modality Driven Promptable Transformer for Automated Parapneumonic Effusion Staging.- Assessing the Social Skills of Children with Autism Spectrum Disorder via Language-Image Pre-training Models.- PPS: Semi-supervised 3D Biomedical Image Segmentation via Pyramid Pseudo-Labeling Supervision.- A Novel Diffusion-Model-Based OCT Image Inpainting Algorithm for Wide Saturation Artifacts.- Only Classification Head is Sufficient for Medical Image Segmentation.- Task-incremental Medical Image Classification with Task-specific Batch Normalization.- Hybrid Encoded Attention Networks for Accurate Pulmonary Artery-Vein Segmentation in Noncontrast CT Images.- Multi-Modality Fusion based Lung Cancer Survival Analysis with Self-Supervised Whole Slide Image Representation Learning.- Incorporating Spiking Neural Network for Dynamic Vision Emotion Analysis.- PAT-Unet: Paired Attention Transformer for Efficient and Accurate Segmentation of 3D Medical Images.- Cell-CAEW: Cell Instance Segmentation based on ConvAttention and Enhanced Watershed.- A Comprehensive Multi-modal Domain Adaptative Aid Framework for Brain Tumor Diagnosis.- Joint Boundary-Enhanced and Topology-Preserving Dual-Path Network for Retinal Layer Segmentation in OCT Images with Pigment Epithelial Detachment.- Spatial Feature Regularization and Label Decoupling based Cross-Subject Motor Imagery EEG Decoding.- Autism spectrum disorder diagnosis using graph neural network based on graph pooling and self-adjust filter.- CDBIFusion: A Cross-Domain Bidirectional Interaction Fusion Network for PET and MRI Images.- LF-LVS: Label-Free Left Ventricular Segmentation for Transthoracic Echocardiogram.- Multi-atlas Representations based on Graph Convolutional Networks for Autism Spectrum Disorder Diagnosis.- MS-UNet: Swin Transformer U-Net with Multi-scale Nested Decoder for Medical Image Segmentation with Small Training Data.- GCUNET: Combining GNN and CNN for Sinogram Restoration in Low-Dose SPECT Reconstruction.- A two-stage whole body bone SPECT scan image inpainting algorithm for residual urine artifacts based on contextual attention.

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Book SynopsisThis book constitutes the proceedings of the 17th Chinese Conference, CCBR 2023, held in Xuzhou, China, during December 1–3, 2023. The 41 full papers included in this volume were carefully reviewed and selected from 79 submissions. The volume is divided in topical sections named: Fingerprint, Palmprint and Vein Recognition; Face Detection, Recognition and Tracking; Affective Computing and Human-Computer Interface; Trustworthy, Privacy and Personal Data Security; Medical and Other Applications. Table of ContentsFingerprint, Palmprint and Vein Recognition.- Face Detection, Recognition and Tracking.- Affective Computing and Human-Computer Interface.- Gait, Iris and Other Biometrics.- Trustyworth, Privacy and Persondal Data Security.- Medical and Other Applications.

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Book SynopsisText in Arabic. What will our life look like with the rapid advancement and development of artificial intelligence? How will AI driven workforces impact the labour market? Can artificial intelligence systems monitor our health and keep our vital elements under control? And the most important and terrifying question of all, will robots become conscious and aware resulting in the ability to take over control of the world? If the answers to these questions interest you, then you need to read this book. Delve into the fourth industrial revolution of artificial intelligence technology to explore its beginnings, importance, branches and the most significant areas of its application, such as in the medical, industrial, economic, and military fields. This book explains how the human brain works and points out the similarities it shares with the ever-evolving computer. Specialists and leading experts share their concerns and the risks about artificial intelligence and discuss their opinions.

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Book SynopsisThis introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the "Knowledge Technologies" course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

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Book SynopsisThis introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the "Knowledge Technologies" course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

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Book SynopsisThis beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book, you will learn how to use Keras and PyTorch in practical applications. It also introduces new chapters on GANs and transformers to reflect the latest trends in deep learning. Beginning Anomaly Detection Using Python-Based Deep Learning begins with an introduction to anomaly detection, its importance, and its applications. It then covers core data science and machine learning modeling concepts before delving into traditional machine learning algorithms such as OC-SVM and Isolation Forest for anomaly detection using scikit-learn. Following this, the authors explain the essentials of machine learning and deep learning, and how to implement multilayer perceptrons for supervised anomaly detection in both Keras and PyTorch. From here, the focus shifts to the applications of deep learning models for anomaly detection, including various types of autoencoders, recurrent neural networks (via LSTM), temporal convolutional networks, and transformers, with the latter three architectures applied to time-series anomaly detection. This edition has a new chapter on GANs (Generative Adversarial Networks), as well as new material covering transformer architecture in the context of time-series anomaly detection. After completing this book, you will have a thorough understanding of anomaly detection as well as an assortment of methods to approach it in various contexts, including time-series data. Additionally, you will have gained an introduction to scikit-learn, GANs, transformers, Keras, and PyTorch, empowering you to create your own machine learning- or deep learning-based anomaly detectors. What You Will Learn Understand what anomaly detection is, why it it is important, and how it is applied Grasp the core concepts of machine learning. Master traditional machine learning approaches to anomaly detection using scikit-kearn. Understand deep learning in Python using Keras and PyTorch Process data through pandas and evaluate your model's performance using metrics like F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications Who This Book Is For Data scientists and machine learning engineers of all levels of experience interested in learning the basics of deep learning applications in anomaly detection.Table of Contents

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Book SynopsisThis book will teach you the underlying concepts of large language models (LLMs), as well as the technologies associated with them. The book starts with an introduction to the rise of conversational AIs such as ChatGPT, and how they are related to the broader spectrum of large language models. From there, you will learn about natural language processing (NLP), its core concepts, and how it has led to the rise of LLMs. Next, you will gain insight into transformers and how their characteristics, such as self-attention, enhance the capabilities of language modeling, along with the unique capabilities of LLMs. The book concludes with an exploration of the architectures of various LLMs and the opportunities presented by their ever-increasing capabilities—as well as the dangers of their misuse. After completing this book, you will have a thorough understanding of LLMs and will be ready to take your first steps in implementing them into your own projects. What You Will Learn Grasp the underlying concepts of LLMs Gain insight into how the concepts and approaches of NLP have evolved over the years Understand transformer models and attention mechanisms Explore different types of LLMs and their applications Understand the architectures of popular LLMs Delve into misconceptions and concerns about LLMs, as well as how to best utilize them Who This Book Is For Anyone interested in learning the foundational concepts of NLP, LLMs, and recent advancements of deep learningTable of ContentsChapter 1: Introduction.- Chapter 2: NLP Through the Ages.- Chapter 3: Transformers.- Chapter 4: What Makes LLMs Large?.- Chapter 5: Popular LLMs.- Chapter 6: Threats, Opportunities, and Misconceptions.

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Book SynopsisChapter 1: Evolution and Significance of Large Language Models.- Chapter 2: What Are Large Language Models?.- Chapter 3: Python for LLMs.- Chapter 4: Python and Other Programming Approaches.- Chapter 5: Basic overview of the components of the LLM architectures.- Chapter 6: Applications of LLMs in Python.- Chapter 7: Harnessing Python 3.11 and Python Libraries for LLM Development.

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Book SynopsisThis book explores the integration of Generative AI within the Banking, Financial Services, and Insurance (BFSI) sector, elucidating its implications, applications, and the future landscape of BFSI. The first part delves into the origins and evolution of Generative AI, providing insights into its mechanics and applications within the BFSI context. It goes into the core technologies behind Generative AI, emphasizing their significance and practical applications. The second part explores how Generative AI intersects with core banking processes, ranging from transactional activities to customer support, credit assessment, and regulatory compliance. It focuses on the digital transformation driving investment banking into the future. It also discusses AI's role in algorithmic trading, client interactions, and regulatory adaptations. It analyzes AI-driven techniques in portfolio management, customer-centric solutions, and the next-generation approach to financial planning and advisory matters. The third part equips you with a structured roadmap for AI adoption in BFSI, highlighting the steps and the challenges. It outlines clear steps to assist BFSI institutions in incorporating Generative AI into their operations. It also raises awareness about the moral implications associated with AI in the BFSI sector. By the end of this book you will understand Generative AI's present and future role in the BFSI sector. What You Will LearnKnow what Generative AI is and its applications in the BFSI sectorUnderstand deep learning and its significance in generative modelsAnalyze the AI-driven techniques in portfolio management and customer-centric solutionsKnowthe future of investment banking and trading with AIKnow the challenges of integrating AI into the BFSI sectorWho This Book Is ForProfessionals in the BFSI and IT sectors, including system administrators and programmers

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Book SynopsisThis book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others. The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications. By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing. What You Will LearnBe able to answer the question: What are Large Language Models?Understand techniques such asprompt engineering, fine-tuning, RAG, and vector databasesKnowthe best practices for effective implementationKnow the metrics and frameworks essential for evaluating the performance of Large Language ModelsWho This Book Is ForAn essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs

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Book SynopsisAs artificial intelligence (AI) rapidly transforms education, tools like ChatGPT and Claude are revolutionizing the way we teach and learn. This book is a groundbreaking book that empowers parents and students to navigate this exciting new frontier, filling a critical gap in the current literature. As the first comprehensive guide to generative AI in education designed for parents and students, Generative AI in Education is positioned to become an indispensable resource. It provides the knowledge and strategies needed to effectively integrate AI into their learning journeys, transforming educational outcomes and preparing students for success in a rapidly changing world.You'll gain a deep understanding of how tools like ChatGPT and Claude work, and how they can be leveraged to support learning across various subjects and grade levels. You'll then see how to create clear, specific, and engaging prompts that elicit valuable responses from AI-powered tools. This book contains all the techniques for tailoring prompts to different learning objectives, styles, and contexts, and how they can use AI tools to support reading comprehension, writing skills, problem-solving, and creative thinking.What You Will LearnApply generative AI in educationCraft effective prompts for personalized learning experiencesUtilize AI tools to support learning, creativity, and problem-solvingWho This Book is ForParents and students who are eager to harness the power of generative AI to enhance learning experiences and prepare for success in an AI-driven future

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Book SynopsisPart 1: Defining Your AI Application.- Chapter 1: Human Flexibility and AI Specialization.- Chapter 2: Meta Systems.- Chapter 3: Prediction Machines.- Part 2: Designing Your AI Application.- Chapter 4: Anatomy of an AI Application.- Chapter 5: Data, Machine Learning, and Reasoners.- Chapter 6: Large Language Models (LLMs).- Chapter 7: AI Agents.- Part 3: Maintaining Your AI Application.- Chapter 8: Testing Your Enterprise AI Application.- Chapter 9: Testing automation for enterprise ai applications.- Chapter 10: Security.- Chapter 11: Information Curation.- Part 4: AI Enabled Teams.- Chapter 12: Remote Work and Reskilling.- Chapter 13: Expert Personas.- Chapter 14: The Role of the AI Handler.- Chapter 15: Legal and Ethical Considerations.

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Book SynopsisChapter 1 Introduction to Analytics.- Chapter 2 Simple Linear Regression.- Chapter 3 Multiple Linear Regression.- Chapter 4 Multivariate Analysis and Prediction.- Chapter 5 Time Series Analysis.

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Book SynopsisThis is a comprehensive exploration into the world of Artificial Intelligence, designed to bridge the gap between theoretical concepts and practical, real-world applications. This book unravels the mystique of AI, breaking down its components into understandable elements. From the early dawn of AI's inception to its current state of rapid evolution, we cover the essential building blocks necessary for leveraging AI in business, and personal development, and understanding its broader impacts on society. Through an engaging conversational format, readers are guided through the intricacies of AI, covering topics such as machine learning, AI governance,, data security, and the ethical challenges facing AI today. This book is an invaluable resource for those looking to understand the fundamentals of AI, its practical applications, and its significant implications for the future. After reading this book, you will be able to integrate AI into your business strategies and learn the intricacies of AI advancements. What You Will Learn:Key concepts and definitions within AI, including types of AI, machine learning, and neural networks and how they are utilized in AI apps like M365 CopilotPractical applications of AI for personal and business growth, focusing on the pillars of using AI to evolve these fronts effectively and sustainablyHow AI is transforming businesses and what organizational shifts must be made to realize the valueNavigating the challenges and ethical considerations in AI to ensure informed and responsible usageWho This Book Is For:Professionals looking to integrate AI into their business strategies or organizations.

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Book SynopsisThis comprehensive guide provides practical strategies for optimizing Generative AI systems to be more sustainable and responsible. As advances in Generative AI such as large language models accelerate, optimizing these resource-intensive workloads for efficiency and alignment with human values grows increasingly urgent. The book starts with the concept of Generative AI and its wide-ranging applications, while also delving into the environmental impact of AI workloads and the growing importance of adopting sustainable AI practices. It then delves into the fundamentals of efficient AI workload management, providing insights into understanding AI workload characteristics, measuring performance, and identifying bottlenecks and inefficiencies. Hardware optimization strategies are explored in detail, covering the selection of energy-efficient hardware, leveraging specialized AI accelerators, and optimizing hardware utilization and scheduling for sustainable operations. You are also guided through software optimization techniques tailored for Generative AI, including efficient model architecture, compression, and quantization methods, and optimization of software libraries and frameworks. Data management and preprocessing strategies are also addressed, emphasizing efficient data storage, cleaning, preprocessing, and augmentation techniques to enhance sustainability throughout the data life cycle. The book further explores model training and inference optimization, cloud and edge computing strategies for Generative AI, energy-efficient deployment and scaling techniques, and sustainable AI life cycle management practices, and concludes with real-world case studies and best practicesBy the end of this book, you will take away a toolkit of impactful steps you can implement to minimize the environmental harms and ethical risks of Generative AI. For organizations deploying any type of generative model at scale, this essential guide provides a blueprint for developing responsible AI systems that benefit society. What You Will LearnUnderstand how Generative AI can be more energy-efficient through improvements such asmodel compression, efficient architecture, hardware optimization, and carbon footprint trackingKnowthe techniques to minimize data usage, includingevaluation, filtering, synthesis, few-shot learning, and monitoring data demands over timeUnderstand spanning efficiency, data minimization, and alignment for comprehensive responsibilityKnow the methods for detecting, understanding, and mitigating algorithmic biases, ensuring diversity in data collection, and monitoring model fairnessWho This book Is ForProfessionals seeking to adopt responsible and sustainable practices in their Generative AI work; leaders and practitioners who need actionable strategies and recommendations that can be implemented directly in real-world systems and organizational workflows; ML engineers and data scientists building and deploying Generative AI systems in industry settings; and researchers developing new generative AI techniques, such as at technology companies or universities

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Book SynopsisChapter 1: Decoding Ecommerce: Business Models for Delivering Value.- Chapter 2: Ecommerce Platform: Journey from Click to Conversion.- Chapter 3: Ecommerce Merchandising: Presenting Curated Products.- Chapter 4: Ecommerce Search: Matching Query to Products.- Chapter 5: Recommendations: Creating Curated Choices.- Chapter 6: Ranking Algorithms: The Science of Sorting.- Chapter 7: Personalization: AI-crafted Personalized Experiences.- Chapter 8: Efficiency: Efficient Ecommerce Deliveries.

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Book SynopsisUnlock the future of software development and empower yourself to elevate your Python applications by harnessing the power of AI as this field continues to grow and evolve. Perfect for beginner to intermediate Python programmers, this book breaks down the essentials of using ChatGPT and OpenAI APIs. You'll start with the basics, learning to authenticate, send prompts, generate responses, test in the Playground, and handle errors with ease. Each chapter includes hands-on exercises that bring concepts to life, demonstrating different API functionalities and practical applications. You'll master models like GPT-4o, GPT-4, GPT-3.5, Whisper, and DALL-E, enabling you to enhance your applications with cutting-edge AI. Discover how generative AI tools like ChatGPT can automate tedious tasks rather than replace jobs. Leverage ChatGPT's powerful Natural Language Processing (NLP) capabilities to handle various formats of unstructured text within your Python apps. Quickly see how easy it is to use ChatGPT as your AI-pair programmer, boosting your productivity and speed. This step-by-step guide will have you creating intelligent chatbots that can automatically process messages from Slack or Discord. With Beginning ChatGPT for Python, you'll master the ChatGPT and OpenAI APIs, building intelligent applications that offer a personalized and engaging user experience. What You'll LearnConnect with the ChatGPT and OpenAI APIs and send effective prompts. Harness parameters like temperature and top_p to create unique and engaging responses from ChatGPT. Create an intelligent assistant bot for Slack that automates tasks and enhances productivity. Develop a bot that can moderate conversations and manage communities on Discord. Add context to your prompts to get more accurate and relevant responses. Who This Book Is ForPython developers and enthusiasts who aspire to employ OpenAI and ChatGPT in the creation of intelligent applications to enhance productivity.

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Book SynopsisChapter 1: Unraveling the Basics of Generative AI.- Chapter 2: Exploring the Transformative Potential of Generative AI.- Chapter 3: Revolutionizing Content: Generative AI in Marketing and Advertising.- Chapter 4: Elevating Customer Interactions with Generative AI.- Chapter 5: Streamlining Operations through Generative AI.- Chapter 6: Pioneering Products with Generative AI.- Chapter 7: Charting the Course: Strategies for Successful Generative AI Implementation.- Chapter 8: Navigating Risks and Legalities of Generative AI.- Chapter 9: Quantifying Success: Evaluating the ROI of Generative AI Initiatives.- Chapter 10: Looking Ahead: Preparing for the Future of Generative AI.

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Book SynopsisAs leaders plan to make significant investments to harness the power of foundational models such as ChatGPT, they need to understand the changes in organizational behaviors required for the successful implementation of such systems. The size, complexity and nature of this new wave of technologies requires a refresh in roles and responsibilities in conventional IT organizations. This book reveals practical and no-nonsense guidance on how to leverage generative AI to transform your business processes and organizational structures to achieve breakthroughs in efficiency, effectiveness and competitive advantage. Written in a lively, engaging, and often humorous style, this work provides practical insights and timely survival skills for leaders with anonymous but real-world experiences and case studies. If you're looking to understand how large language foundation models such as ChatGPT are reshaping managerial roles and organizational structures, and how they can leverage this knowledge to survive and thrive in this brave new world then Organizing for Generative AI and the Productivity Revolution is the book for you. What You Will Learn Review the key changes in current state roles and responsibilities that are required to successfully deploy generative AI systemsExamine the organizational reporting structures and associated incentives that form a strong generative AI systemUnderstand the financial, regulatory, and operational risks created by organizational behavioral issues that arise when organizations build and deploy large language modelsCompare the strategic differences in emerging versus traditional organizational behaviors, incentives, roles and responsibilitiesWho This Book Is ForExecutives and team leaders at enterprises large and small. The book addresses an important topic: how to set up an organization for success, particularly in Generative AI. Generative AI brings new challenges to organizations in terms of how to structure the organization for success, mitigating risks, software development lifecycle, and tracking ROI. I could think of no better person to tackle these issues than Arthur O'Connor, who has extensive experience in technology within some of the largest enterprises in Wall Street, complemented by his academic background. He brings an insightful and unique perspective for technology leaders who want to set up their organizations for success in Generative AI.- Joseph Sabelja, Generative AI Firmwide Platform Lead, J P Morgan

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Book SynopsisChapter 1: Introduction: General Purpose Robotics.- Chapter 2: Robot Perception: Sensors and Image Processing.- Chapter 3: Robot Perception: 3D Data and Sensor Fusion.- Chapter 4: Foundation Models in Robotics.- Chapter 5: Simulation.- Chapter 6: Mapping, Localization, and Navigation.- Chapter 7: Reinforcement Learning and Control.- Chapter 8: Self Driving Cars.- Chapter 9: Industrial Robotics.- Chapter 10: Humanoid Robotics.- Chapter 11: Data-Driven Robotics in Practice.

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Book SynopsisThis book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios. The book begins with an introduction to the core concepts of deep learning. It delves into topics such as transfer learning, multi-task learning, and end-to-end learning, providing insights into various deep learning models and their real-world applications. Next, it covers neural networks, progressing from single-layer perceptrons to multi-layer perceptrons, and solving the complexities of backpropagation and gradient descent. It explains optimizing model performance through effective techniques, addressing key considerations such as hyperparameters, bias, variance, and data division. It also covers convolutional neural networks (CNNs) through two comprehensive chapters, covering the architecture, components, and significance of kernels implementing well-known CNN models such as AlexNet and LeNet. It concludes with exploring autoencoders and generative models such as Hopfield Networks and Boltzmann Machines, applying these techniques to a diverse set of practical applications. These applications include image classification, object detection, sentiment analysis, COVID-19 detection, and ChatGPT. By the end of this book, you will have gained a thorough understanding of deep learning, from its fundamental principles to its innovative applications, enabling you to apply this knowledge to solve a wide range of real-world problems. What You Will LearnWhat are deep neural networks?What is transfer learning, multi-task learning, and end-to-end learning?What are hyperparameters, bias, variance, and data division?What are CNN and RNN?Who This Book Is ForMachine learning engineers, data scientists, AI practitioners, software developers, and engineers interested in deep learning

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Book SynopsisChapter 1: Introduction.- Chapter 2: Obtaining Data.- Chapter 3: ETL Pipeline.- Chapter 4: Exploratory Data Analysis.- Chapter 5: Machine Learning Models.- Chapter 6: Evaluating Models.- Chapter 7: When To Use Machine Learning Models.- Chapter 8: Where Machine Learning Models Live.- Chapter 9: Telemetry.- Chapter 10: Adversaries and Abuse.- Chapter 11: Working With Models.

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Book SynopsisPart 1: Foundations and Case Study Introduction.- Chapter 1: NLP Essentials.- Chapter 2: Oracle Cloud for NLP.- Chapter 3: Healthcare NLP Case Study.- Part2: Case Study Implementation.- Chapter 4: Tenancy Preparation.- Chapter 5: Dataset Preparation.- Chapter 6: Model Fine-tuning.- Part 3: Case Study Deployment and Wrap-Up.- Chapter 7: Model Deployment and Monitoring.- Chapter 8: MLOps and Conclusion.

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Book SynopsisChapter 1: Introduction to MLOps.- Chapter 2: Foundations of MLOps on AWS.- Chapter 3: Operational Excellence in MLOps.- Chapter 4: Security in MLOps.- Chapter 5: Reliability in MLOps.- Chapter 6: Performance Efficiency in MLOps.- Chapter 7: Cost Optimization in MLOps.- Chapter 8 MLOps Best Practices and Case Studies.- Chapter 9: MLOps for GenAI.- Chapter 10: Future Trends in MLOps.

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Book Synopsis

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