Neural networks and fuzzy systems Books
Emerald Publishing Limited Self-Learning and Adaptive Algorithms for
Book SynopsisIn today’s data-driven world, more sophisticated algorithms for data processing are in high demand, mainly when the data cannot be handled with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla, Microsoft, and Facebook in their projects and applications. In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear. Including research relevant to those studying cybernetics, applied mathematics, statistics, engineering, and bioinformatics who are working in the areas of machine learning, artificial intelligence, complex system modeling and analysis, neural networks, and optimization, this is an ideal read for anyone interested in learning more about the fascinating new developments in machine learning.Trade ReviewThis guide explains how to apply methods using systems built by a combination of the neural network approach and fuzzy logic (neuro-fuzzy systems) to solve practical data classification problems in business. It describes methods aimed at handling the main types of uncertainties in data, using adaptive methods of fuzzy clustering; the use of Kohonen maps and their ensembles for fuzzy clustering tasks; and simulation results of these neuro-fuzzy architectures, their learning methods, self-organization, and clustering procedures. -- Annotation ©2019 * (protoview.com) *Table of ContentsIntroduction 1. Review of the Problem Area 2. Adaptive Methods of Fuzzy Clustering 3. Kohonen Maps and their Ensembles for Fuzzy Clustering Tasks 4. Simulation Results and Solutions for Practical Tasks Conclusion
£43.69
Imperial College Press Neural Nets And Chaotic Carriers (2nd Edition)
Book SynopsisNeural Nets and Chaotic Carriers develops rational principles for the design of associative memories, with a view to applying these principles to models with irregularly oscillatory operation so evident in biological neural systems, and necessitated by the meaninglessness of absolute signal levels.Design is based on the criterion that an associative memory must be able to cope with “fading data”, i.e., to form an inference from the data even as its memory of that data degrades. The resultant net shows striking biological parallels. When these principles are combined with the Freeman specification of a neural oscillator, some remarkable effects emerge. For example, the commonly-observed phenomenon of neuronal bursting appears, with gamma-range oscillation modulated by a low-frequency square-wave oscillation (the “escapement oscillation”). Bridging studies and new results of artificial and biological neural networks, the book has a strong research character. It is, on the other hand, accessible to non-specialists for its concise exposition on the basics.Table of ContentsOpening and Themes:Introduction and Aspirations;Optimal Statistical Procedures;Linear Links and Nonlinear Knots: The Basic Neural Net;Bifurcations and Chaos; Associative and Storage Memories:What is a Memory? The Hamming and Hopfield Nets;Compound and SpuriousA" Traces;Preserving Plasticity: A Bayesian Approach;The Key Task: The Fixing of Fading Data, Conclusions I;Performance of the Probability-Maximising Algorithm;Other Memories - Other Considerations; Oscillatory Operation and the Biological Model:Neuron Models and Neural Masses;Freeman Oscillators - Solo and in Concert;Associative Memories Incorporating the Freeman Oscillator;Olfactory Comparisons, Conclusions II;Transmission Delays;
£76.95
Edward Elgar Publishing Ltd Nonlinear Economic Models: Cross-sectional, Time
Book SynopsisNonlinear modelling has become increasingly important and widely used in economics. This valuable book brings together recent advances in the area including contributions covering cross-sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural network and genetic algorithm models of financial markets. Attention is given to the development of theoretical models as well as estimation and testing methods with a wide range of applications in micro and macroeconomics, labour and finance.The book provides valuable introductory material that is accessible to students and scholars interested in this exciting research area, as well as presenting the results of new and original research. Nonlinear Economic Models provides a sequel to Chaos and Nonlinear Models in Economics by the same editors.Trade Review'This collection provides valuable introductory material that is accessible to students and scholars interested in this research area.' -- Business HorizonsTable of ContentsContents: Part I: Introduction 1. Nonlinear Modelling: An Introduction Part II: Cross-sectional Applications 2. A Model of Income Distribution 3. Truncated Distribution Families 4. Betit: A Flexible Binary Choice Model 5. Estimation of Generalised Distributions 6. Age and the Distribution of Earnings 7. Count Data and Discrete Distributions Part III: Time Series Applications 8. A Model of the Real Exchange Rate 9. Jump Models and Higher Moments 10. A Topological Test of Chaos 11. Genetic Algorithms and Trading Rules Part IV: Neural Network Applications 12. Artificial Neural Networks 13. An ANN Model of the Stock Market 14. Exchange Rate Forecasting Models Index
£111.00
Springer Nature Switzerland AG Proceedings of the 22nd Engineering Applications
Book SynopsisThis book contains the proceedings of the 22nd EANN “Engineering Applications of Neural Networks” 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent – long short-term memory. The application domains are related to: Anomaly detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.Table of ContentsAutomatic Facial Expression Neutralisation Using Generative Adversarial Network.- Creating Ensembles of Generative Adversarial Network Discriminators for One-class Classification.- A Hybrid Deep Learning Ensemble for Cyber Intrusion Detection.- Anomaly Detection by Robust Feature Reconstruction.- Deep Learning of Brain Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia.- Deep learning topology-preserving EEG-based images for autism detection in infants.- Improving the Diagnosis of Breast Cancer by Combining Visual and Semantic Feature Descriptors.- Liver cancer trait detection and classification through Machine Learning on smart mobile devices.
£224.99
Springer Nature Switzerland AG Fuzzy Information Processing 2020: Proceedings of
Book SynopsisThis book describes how to use expert knowledge—which is often formulated by using imprecise (fuzzy) words from a natural language. In the 1960s, Zadeh designed special "fuzzy" techniques for such use. In the 1980s, fuzzy techniques started controlling trains, elevators, video cameras, rice cookers, car transmissions, etc. Now, combining fuzzy with neural, genetic, and other intelligent methods leads to new state-of-the-art results: in aerospace industry (from drones to space flights), in mobile robotics, in finances (predicting the value of crypto-currencies), and even in law enforcement (detecting counterfeit banknotes, detecting online child predators and in creating explainable AI systems). The book describes these (and other) applications—as well as foundations and logistics of fuzzy techniques. This book can be recommended to specialists—both in fuzzy and in various application areas—who will learn latest techniques and their applications, and to students interested in innovative ideas.Table of ContentsPowerset operators in categories with fuzzy relations dened by monads.- Improved Fuzzy Q-Learning with Replay Memory.- The ulem package: underlining for emphasis.- A Dynamic Hierarchical Genetic-Fuzzy Sugeno Network.- Fuzzy Mathematical Morphology and Applications in Image Processing.
£179.99
Springer International Publishing AG Artificial Neural Networks in Pattern Recognition: 10th IAPR TC3 Workshop, ANNPR 2022, Dubai, United Arab Emirates, November 24–26, 2022, Proceedings
Book SynopsisThis book constitutes the refereed proceedings of the 10th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2022, held in Dubai, UAE, in November 2022. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The conference presents papers on subject such as pattern recognition and machine learning based on artificial neural networks. Table of ContentsTransformer-Encoder generated context-aware embeddings for spell correction.- Graph Augmentation for Neural Networks Using Matching-Graphs.- Wavelet Scattering Transform Depth Benefit, An Application for Speaker Identification.- Assessment of Pharmaceutical Patent Novelty using Siamese Neural Network.- A Review of Capsule Networks in Medical Image Analysis.- Multi-stage Bias Mitigation for Individual Fairness in Algorithmic Decisions.- Introducing an Atypical Loss: A Perceptual Metric Learning for Image Pairing.- A Study on the Autonomous Detection of Impact Craters.- Minimizing Cross Intersections in Graph Drawing via Linear Splines.- Sequence-to-Sequence CNN-BiLSTM Based Glottal Closure Instant Detection from Raw Speech.- Do Minimal Complexity Least Squares Support Vector Machines Work?.- A Novel Representation of Graphical Patterns for Graph Convolution Networks.- Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi Utilization of Vision Transformer for Classification and Ranking of Video Distortions.- White Blood Cell Classification of Porcine Blood Smear Images.- Medical Deepfake Detection using 3-Dimensional Neural Learning.
£47.49
Springer International Publishing AG Shallow and Deep Learning Principles: Scientific,
Book SynopsisThis book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least three layers that must be established together with cells, one of which is input, the other is output, and the third is a hidden (intermediate) layer. For this, the author states, it is necessary to develop an architecture that will not model mathematical rules but only the action and response variables that control the event and the reactions that may occur within it. The book explains the reasons and necessity of each ANN model, considering the similarity to the previous methods and the philosophical - logical rules.Table of ContentsIntroduction.- Philosophical and Logical Principles in Science.- Uncertainty and Modeling Principles.- Mathematical Modeling Principles.- Genetic Algorithm.- Artificial Neural Networks.- Artıfıcıal Intellıgence.- Machıne Learnıng.- Deep Learning.- Conclusion.
£118.99
Springer International Publishing AG Neural Networks and Deep Learning: A Textbook
Book SynopsisThis book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. The chapters of this book span three categories: The basics of neural networks: The backpropagation algorithm is discussed in Chapter 2.Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 4 and 5. Chapters 6 and 7 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 8, 9, and 10 discuss recurrent neural networks, convolutional neural networks, and graph neural networks. Several advanced topics like deep reinforcement learning, attention mechanisms, transformer networks, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 11 and 12. The textbook is written for graduate students and upper under graduate level students. Researchers and practitioners working within this related field will want to purchase this as well.Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.The second edition is substantially reorganized and expanded with separate chapters on backpropagation and graph neural networks. Many chapters have been significantly revised over the first edition.Greater focus is placed on modern deep learning ideas such as attention mechanisms, transformers, and pre-trained language models.Table of ContentsAn Introduction to Neural Networks.- The Backpropagation Algorithm.- Machine Learning with Shallow Neural Networks.- Deep Learning: Principles and Training Algorithms.- Teaching a Deep Neural Network to Generalize.- Radial Basis Function Networks.- Restricted Boltzmann Machines.- Recurrent Neural Networks.- Convolutional Neural Networks.- Graph Neural Networks.- Deep Reinforcement Learning.- Advanced Topics in Deep Learning.
£53.99
Springer International Publishing AG Neural Information Processing: 29th International
Book SynopsisThe three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022.The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications.The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.Table of ContentsTheory and Algorithms.- Solving Partial Differential Equations using Point-based Neural Networks.- Patch Mix Augmentation with Dual Encoders for Meta-Learning.- Tacit Commitments Emergence in Multi-agent Reinforcement Learning.- Saccade Direction Information Channel.- Shared-Attribute Multi-Graph Clustering with Global Self-Attention.- Mutual Diverse-Label Adversarial Training.- Multi-Agent Hyper-Attention Policy Optimization.- Filter Pruning via Similarity Clustering for Deep Convolutional Neural Networks.- FPD: Feature Pyramid Knowledge Distillation.- An effective ensemble model related to incremental learning in neural machine translation.- Local-Global Semantic Fusion Single-shot Classification Method.- Self-Reinforcing Feedback Domain Adaptation Channel.- General Algorithm for Learning from Grouped Uncoupled Data and Pairwise Comparison Data.- Additional Learning for Joint Probability Distribution Matching in BiGAN.- Multi-View Self-Attention for Regression Domain Adaptation with Feature Selection.- EigenGRF: Layer-Wise Eigen-Learning for Controllable Generative Radiance Fields.- Partial Label learning with Gradually Induced Error-Correction Output Codes.- HMC-PSO: A Hamiltonian Monte Carlo and Particle Swarm Optimization-based optimizer.- Heterogeneous Graph Representation for Knowledge Tracing.- Intuitionistic fuzzy universum support vector machine.- Support vector machine based models with sparse auto-encoder based features for classification problem.- Selectively increasing the diversity of GAN-generated samples.- Cooperation and Competition: Flocking with Evolutionary Multi-Agent Reinforcement Learning.- Differentiable Causal Discovery Under Heteroscedastic Noise.- IDPL: Intra-subdomain adaptation adversarial learning segmentation method based on Dynamic Pseudo Labels.- Adaptive Scaling for U-Net in Time Series Classification.- Permutation Elementary Cellular Automata: Analysis and Application of Simple Examples.- SSPR: A Skyline-Based Semantic Place Retrieval Method.- Double Regularization-based RVFL and edRVFL Networks for Sparse-Dataset Classification.- Adaptive Tabu Dropout for Regularization of Deep Neural Networks.- Class-Incremental Learning with Multiscale Distillation for Weakly Supervised Temporal Action Localization.- Nearest Neighbor Classifier with Margin Penalty for Active Learning.- Factual Error Correction in Summarization with Retriever-Reader Pipeline.- Context-adapted Multi-policy Ensemble Method for Generalization in Reinforcement Learning.- Self-attention based multi-scale graph convolutional networks.- Synesthesia Transformer with Contrastive Multimodal Learning.- Context-based Point Generation Network for Point Cloud Completion.- Temporal Neighborhood Change Centrality for Important Node Identification in Temporal Networks.- DOM2R-Graph: A Web Attribute Extraction Architecture with Relation-aware Heterogeneous Graph Transformer.- Sparse Linear Capsules for Matrix Factorization-based Collaborative Filtering.- PromptFusion: a Low-cost Prompt-based Task Composition for Multi-task Learning.- A fast and efficient algorithm for filtering the training dataset.- Entropy-minimization Mean Teacher for Source-Free Domain Adaptive Object Detection.- IA-CL: A Deep Bidirectional Competitive Learning Method for Traveling Salesman Problem.- Boosting Graph Convolutional Networks With Semi-Supervised Training.- Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs.- VAAC: V-value Attention Actor-Critic for Cooperative Multi-agent Reinforcement Learning.- An Analytical Estimation of Spiking Neural Networks Energy Efficiency.- Correlation Based Semantic Transfer with Application to Domain Adaptation.- Minimum Variance Embedded Intuitionistic Fuzzy Weighted Random Vector Functional Link Network.- Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction.
£75.99
£75.05
De Gruyter Meta-heuristic Optimization Techniques:
Book SynopsisThis book offers a thorough overview of the most popular and researched meta-heuristic optimization techniques and nature-inspired algorithms. Their wide applicability makes them a hot research topic and an effi cient tool for the solution of complex optimization problems in various fi elds of sciences, engineering, and in numerous industries.
£88.50
Peter Lang AG Activation Functions: Activation Functions in
Book SynopsisThis book describes the functions frequently used in deep neural networks. For thispurpose, 37 activation functions are explained both mathematically and visually, andgiven with their LaTeX implementations due to their common use in scientific articles.Table of ContentsIntroduction — Machine Learning — Neural Networks — Activation Functions — Monotonic Activation Functions — Periodic Activation Functions — Bias Unit .
£20.52
Atlantis Press Web-based Information Technologies And
Book SynopsisThis book is devoted to the emerging and novel concepts, architectures and methodologies for creating an interconnected world where information can be exchanged easily, tasks can be processed collaboratively, and communities of users with similar interests can be formed transcending borders, while addressing the increasingly pervasive security threats. This book is a collection of the best papers from WITDS Track of IEEE SITIS 2008. All the chapters are newly extended versions of the original papers. The book contains four parts; the first part is devoted to Ad Hoc and Routing Protocols where novel algorithms are proposed for ad hoc networks; the second part focuses on security and policies and the various innovative solutions; the third part covers efficient algorithms for web services; the fourth part features the various intelligent systems for agent systems, smart home environment, and service-driven applications.
£93.60
World Scientific Publishing Co Pte Ltd Introduction To Control Systems, An (2nd Edition)
Book SynopsisThis significantly revised edition presents a broad introduction to Control Systems and balances new, modern methods with the more classical. It is an excellent text for use as a first course in Control Systems by undergraduate students in all branches of engineering and applied mathematics. The book contains: A comprehensive coverage of automatic control, integrating digital and computer control techniques and their implementations, the practical issues and problems in Control System design; the three-term PID controller, the most widely used controller in industry today; numerous in-chapter worked examples and end-of-chapter exercises. This second edition also includes an introductory guide to some more recent developments, namely fuzzy logic control and neural networks.Table of ContentsSystem representations; system response using differential equations; system stability and performance; frequency response analysis; state equations; state variable feedback; digital control; computng methods; three-term controllers.
£65.55
World Scientific Publishing Co Pte Ltd Neural Adaptive Control Technology
Book SynopsisThis book is an outgrowth of the workshop on Neural Adaptive Control Technology, NACT I, held in 1995 in Glasgow. Selected workshop participants were asked to substantially expand and revise their contributions to make them into full papers.The workshop was organised in connection with a three-year European Union funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland). A major aim of the NACT project is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from Daimler-Benz.In the book emphasis is put on development of sound theory of neural adaptive control for nonlinear control systems, but firmly anchored in the engineering context of industrial practice. Therefore the contributors are both renowned academics and practitioners from major industrial users of neurocontrol.Table of ContentsPart 1 Neural adaptive control technology: discrete-time neural model structures for continuous nonlinear systems - fundamental properties and control aspects, J.C. Kalkkuhl and K.J. Hunt; continuous-time local model networks, P.J. Gawthrop; nonuniform sampling approach to control systems modelling with feedforward networks, R. Zbikowski and A. Dzielinski. Part 2 Nonlinear control fundamentals for neural networks: geometric methods in nonlinear control theory - a survey, W. Respondek; local reachability and local controllability of a class of 2-D bilinear systems, T. Kaczorek; stable adaptive control of a general class of nonlinear systems, T.A. Johansen and M.M. Polycarpou. Part 3 Neural techniques and applications: process modelling with state-space neural predictors, I. Rivals et al; an approach to intelligent identification and control on nonlinear dynamic systems, applied to optimizing lean-burn engine controls, D.A. Sofge and D.L. Elliott; improved CMAC-type memories for learning control, W.S. Mischo; interpretation and analysis of empirical models identified with the ASMOD algorithm, T. Kavli and G. Lines.
£103.50
World Scientific Publishing Co Pte Ltd Introduction To Control Systems, An (2nd Edition)
Book SynopsisThis significantly revised edition presents a broad introduction to Control Systems and balances new, modern methods with the more classical. It is an excellent text for use as a first course in Control Systems by undergraduate students in all branches of engineering and applied mathematics. The book contains: A comprehensive coverage of automatic control, integrating digital and computer control techniques and their implementations, the practical issues and problems in Control System design; the three-term PID controller, the most widely used controller in industry today; numerous in-chapter worked examples and end-of-chapter exercises. This second edition also includes an introductory guide to some more recent developments, namely fuzzy logic control and neural networks.
£34.20
World Scientific Publishing Co Pte Ltd Adaptive Neural Network Control Of Robotic
Book SynopsisRecently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an “on-and-off” fashion. This book is dedicated to issues on adaptive control of robots based on neural networks. The text has been carefully tailored to (i) give a comprehensive study of robot dynamics, (ii) present structured network models for robots, and (iii) provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.
£108.00
World Scientific Publishing Co Pte Ltd Information Theoretic Neural Computation
Book SynopsisIn order to develop new types of information media and technology, it is essential to model complex and flexible information processing in living systems. This book presents a new approach to modeling complex information processing in living systems. Traditional information-theoretic methods in neural networks are unified in one framework, i.e. α-entropy. This new approach will enable information systems such as computers to imitate and simulate human complex behavior and to uncover the deepest secrets of the human mind.Table of ContentsInformation in neural networks; information minimization; information maximization; constrained information maximization; neural feature detectors; information maximization and minimization; information controller; information control by alpha-entropy; integrated information processing systems.
£90.90
World Scientific Publishing Co Pte Ltd Principles Of Artificial Neural Networks: Basic
Book SynopsisThe field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained.The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.
£130.50
World Scientific Publishing Co Pte Ltd Fuzzy Systems To Quantum Mechanics
Book SynopsisThis unique compendium represents important action of fuzzy systems to quantum mechanics. From fuzzy sets to fuzzy systems, it also gives clear descriptions on the development on fuzzy logic, where the most important result is the probability presentation of fuzzy systems.The important conclusions on fuzzy systems are used in the study of quantum mechanics, which is a very new idea. Eight important conclusions are obtained. The author has proved that mass-point motions in classical mechanics must have waves, which means that any mass-point motion in classical mechanics has wave mass-point dualism as well as any microscopic particle motion must have wave-particle dualism. Based on this conclusion, it has been proven that classical mechanics and quantum mechanics are unified.
£130.50
World Scientific Publishing Co Pte Ltd Granular Video Computing: With Rough Sets, Deep
Book SynopsisThis volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.
£76.00
World Scientific Publishing Co Pte Ltd Subcritical Brain, The: A Synergy Of Segregated
Book SynopsisHave over a hundred years of brain research revealed all its secrets? This book is motivated by a realization that cortical structure and behavior can be explained by a synergy of seemingly different mathematical notions: global attractors, which define non-invertible neural firing rate dynamics, random graphs, which define connectivity of neural circuit, and prime numbers, which define the dimension and category of cortical operation. Quantum computation is shown to ratify the main conclusion of the book: loosely connected small neural circuits facilitate higher information storage and processing capacities than highly connected large circuits. While these essentially separate mathematical notions have not been commonly involved in the evolution of neuroscience, they are shown in this book to be strongly inter-related in the cortical arena. Furthermore, neurophysiological experiments, as well as observations of natural behavior and evidence found in medical testing of neurologically impaired patients, are shown to support, and to be supported by the mathematical findings.Related Link(s)
£85.50
World Scientific Publishing Company Synesthesia Decodes Innovation The Dante Effect
Book Synopsis
£139.50
World Scientific Publishing Co Pte Ltd Wavelets In Soft Computing
Book SynopsisThe comprehensive compendium furnishes a quick and efficient entry point to many multiresolution techniques and facilitates the transition from an idea into a real project. It focuses on methods combining several soft computing techniques (fuzzy logic, neural networks, genetic algorithms) in a multiresolution framework.Illustrated with numerous vivid examples, this useful volume gives the reader the necessary theoretical background to decide which methods suit his/her needs.New materials and applications for multiresolution analysis are added, including notable research topics such as deep learning, graphs, and network analysis.
£90.00
World Scientific Publishing Co Pte Ltd Intelligent Analysis Of Fundus Images: Methods
Book SynopsisThis comprehensive compendium designs deep neural network models and systems for intelligent analysis of fundus imaging. In response to several blinding fundus diseases such as Retinopathy of Prematurity (ROP), Diabetic Retinopathy (DR) and Macular Edema (ME), different image acquisition devices and fundus image analysis tasks are elaborated.From the actual fundus disease analysis tasks, various deep neural network models and experimental results are constructed and analyzed. For each task, an actual system for clinical application is developed.This useful reference text provides theoretical and experimental reference basis for AI researchers, system engineers of intelligent medicine and ophthalmologists.
£76.00
World Scientific Publishing Company Analysis and Visualization of Discrete Data Using
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£76.00
Springer Verlag, Singapore Hesitant Fuzzy Set: Theory and Extension
Book SynopsisCovering a wide range of notions concerning hesitant fuzzy set and its extensions, this book provides a comprehensive reference to the topic. In the case where different sources of vagueness appear simultaneously, the concept of fuzzy set is not able to properly model the uncertainty, imprecise and vague information. In order to overcome such a limitation, different types of fuzzy extension have been introduced so far. Among them, hesitant fuzzy set was first introduced in 2010, and the existing extensions of hesitant fuzzy set have been encountering an increasing interest and attracting more and more attentions up to now. It is not an exaggeration to say that the recent decade has seen the blossoming of a larger set of techniques and theoretical outcomes for hesitant fuzzy set together with its extensions as well as applications.As the research has moved beyond its infancy, and now it is entering a maturing phase with increased numbers and types of extensions, this book aims to give a comprehensive review of such researches. Presenting the review of many and important types of hesitant fuzzy extensions, and including references to a large number of related publications, this book will serve as a useful reference book for researchers in this field.Table of ContentsChapter 1: Hesitant Fuzzy Set.- Chapter 2: Hesitant Fuzzy Linguistic Term Set.- Chapter 3: Neutrosophic Hesitant Fuzzy Set.- Chapter 4: Pythagorean Hesitant Fuzzy Set.- Chapter 5: q-Rung Orthopair Hesitant Fuzzy Set.- Chapter 6: Probabilistic Hesitant Fuzzy Set.- Chapter 7: Type 2 Hesitant Fuzzy Set.- Chapter 8: Hesitant Bipolar Fuzzy Set.- Chapter 9: Cubic Hesitant Fuzzy Set.- Chapter 10: Complex Hesitant Fuzzy Set.- Chapter 11: Picture Hesitant Fuzzy Set.- Chapter 12: Spherical Hesitant Fuzzy Set.
£98.99
World Scientific Publishing Co Pte Ltd Handbook On Sensor Networks
Book SynopsisSensor networks have many interesting applications with great utility; however, their actually deployment and realization rely on continuous innovations and solutions to many challenging problems. Thus, sensor networks have recently attracted the attention of many researchers and practitioners. The compilation of the Handbook on Sensor Networks will meet the demand of the sensor network community for a comprehensive reference and summary of the current state of the area.The Handbook on Sensor Networks is a collection of approximately 40 chapters on sensor network theory and applications. The book spans a wide spectrum and includes topics in medium access control, routing, security and privacy, coverage and connectivity, modeling and simulations, multimedia, energy efficiency, localization and tracking, design and implementation, as well as sensor network applications.Table of ContentsMedium Access Control; Monitoring, Data Gathering, and Localization; Design and Architecture; Energy Efficiency; Routing; Multimedia; Security; Theory and Classical Problems.
£164.70
World Scientific Publishing Co Pte Ltd Selected Topics In Communication Networks And
Book SynopsisCommunication networks and distributed system technologies are undergoing rapid advancements. The last few years have experienced a steep growth in research on different aspects in these areas. Even though these areas hold great promise for our future, there are several challenges that need to be addressed. This review volume discusses important issues in selected emerging and matured topics in communication networks and distributed systems. It will be a valuable reference for students, instructors, researchers, engineers and strategists in this field.Table of ContentsNetwork and Information Security; Network Architecture; Mobile Ad Hoc, Sensor and Mesh Networks; Mobile Computing; Network Protocol Design and Analysis; Protocol Verification and Validation; Network Testing; Network Management; Reliability and Fault Tolerance; Multimedia Networking; Quality of Service; Routing and Traffic Engineering; Web Services; Network Programming; Grid Computing; Cluster Computing; Real-Time and Embedded Systems; Internet Computing.
£229.50
World Scientific Publishing Co Pte Ltd Deep Learning Neural Networks: Design And Case
Book SynopsisDeep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research.
£69.35
World Scientific Publishing Co Pte Ltd Deep Learning Neural Networks: Design And Case
Book SynopsisDeep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research.
£38.00
World Scientific Publishing Co Pte Ltd Fuzzy Logic Theory And Applications: Part I And
Book SynopsisNowadays, voluminous textbooks and monographs in fuzzy logic are devoted only to separate or some combination of separate facets of fuzzy logic. There is a lack of a single book that presents a comprehensive and self-contained theory of fuzzy logic and its applications.Written by world renowned authors, Lofti Zadeh, also known as the Father of Fuzzy Logic, and Rafik Aliev, who are pioneers in fuzzy logic and fuzzy sets, this unique compendium includes all the principal facets of fuzzy logic such as logical, fuzzy-set-theoretic, epistemic and relational. Theoretical problems are prominently illustrated and illuminated by numerous carefully worked-out and thought-through examples.This invaluable volume will be a useful reference guide for academics, practitioners, graduates and undergraduates in fuzzy logic and its applications.
£130.50
World Scientific Publishing Co Pte Ltd Fuzzy Logic-based Material Selection And
Book SynopsisThis unique compendium presents a comprehensive and self-contained theory of material development under imperfect information and its applications. The book describes new approaches to synthesis and selection of materials with desirable characteristics. Such approaches provide the ability of systematic and computationally effective analysis in order to predict composition, structure and related properties of new materials.The volume will be a useful advanced textbook for graduate students. It is also suitable for academicians and practitioners who wish to have fundamental models in new material synthesis and selection.
£85.50
World Scientific Publishing Co Pte Ltd Vision: Images, Signals And Neural Networks -
Book SynopsisAt the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hérault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio-temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision.Table of ContentsFrom Photons to Images; The Visual System of Primate; Basic Model of the Retina; Neuromorphic Circuits and Motion Estimation; Color Processing in the Retina; Non-Linear, Irregular and Non-Stationary Processes; Cortical Processing of Images.
£51.30
World Scientific Publishing Co Pte Ltd Integration Of Swarm Intelligence And Artificial
Book SynopsisThis book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning.To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.Table of ContentsTheoretical Foundations of Both SI and ANN; Advances of SI and ANN; Hybridization of SI and ANN; Applications.
£95.40
World Scientific Publishing Co Pte Ltd Reasoning About Fuzzy Temporal And Spatial
Book SynopsisThis book comprehensively studies fuzzy temporal and spatial information, starting from the basics on fuzzy set theory and temporal/spatial reasoning, the development of a new model to represent fuzzy temporal/spatial information, the study of efficient and complete reasoning algorithms, and their application in an information retrieval context. This useful volume presents the first approach that goes beyond merely representing information, by thoroughly addressing a variety of reasoning tasks. It also focuses on applications in the domain of information retrieval, and demonstrating the practical importance of the proposed framework.Table of ContentsRelatedness of Fuzzy Sets, Fuzzification of Allen's Temporal Interval Relation; Reasoning About Qualitative Relations Between Fuzzy Intervals; Temporal Information Retrieval with Vague Events; Representation and Composition of Fuzzy Spatial Relations; Fuzzification of the Region Connection Calculus; Reasoning in the Fuzzy Region Connection Calculus; Geographic Information Retrieval with Vague Regions.
£175.50
World Scientific Publishing Co Pte Ltd Connectionist Models Of Neurocognition And
Book SynopsisThis volume collects together most of the papers presented at the Twelfth Neural Computation and Psychology Workshop (NCPW12) held in 2010 at Birkbeck College (England). The conference invited submissions on neurocomputational models of all cognitive and psychological processes. The special theme of this conference was “From Theory to Applications”, which allowed submissions of pure theoretical work and of pure applied work. This topic extended the boundaries of the conference and highlighted the extent to which computational models of cognition and models in general are integrated in the cognitive sciences.The chapters in this book cover a wide range of research topics in neural computation and psychology, including cognitive development, language processing, higher-level cognition, but also ecology-based modeling of cognition, philosophy of science, and real-world applications.Table of ContentsPerceptual Processing; Categorization; Attention; Language Processing; High-Level Cognition; Philosophy of Computational Science.
£120.60
World Scientific Publishing Co Pte Ltd Methods For Decision Making In An Uncertain
Book SynopsisThis book contains a selection of the papers presented at the XVII SIGEF Congress. It presents fuzzy logic, neural networks and other intelligent techniques applied to economic and business problems. This book is very useful for researchers and graduate students aiming to introduce themselves to the field of quantitative techniques for overcoming uncertain environments. The contributors are experienced scholars of different countries who offer real world applications of these mathematical techniques.Table of ContentsIntroduction: The Spanish School of Fuzzy Economics (Jaime Gil-Aluja); Theoretical Foundations: Specific Max. Traveling Salesman Problems (Raul O Dichiara, Blanca I Niel); Solving Fuzzy Mathematical Programming: A Parametric Approach (Ricardo Coelho Silva, Carlos Cruz Corona, Jose L Verdegay); Study of Fuzzy Model With Constant Development (Xavier Bertran, Narcis Clara, Dolors Corominas); Finance: A Decision Support System for Scoring Distressed Debts and Planning their Collection (Gianluca Murgia, Simone Sbrilli); An Assessment of Abnormal Returns in Socially Responsible Firms Using Fuzzy Jensen's Alpha Values (Klender Aimer Cortez Alejandro, Martha del Pilar Rodriguez Garcia, Maria Teresa Sorrosal-Forradellas); Return and Risk: The Spanish Public Debt Market (Jose M Brotons, Antonio Terceno, M Gloria Barbera-Marine); Time Analysis of Responsibility in Finance (David Ceballos); Online Change-Point Detection in Financial Time Series: Challenges and Experimental Evidence with Frequentist and Bayesian Setups (Vasile Georgescu); Application of a Fuzzy Model of Economic-Financial Diagnosis to SMEs (Antonio Tercenno, Hernan Vigier, Valeria Scherger); Economics and Politics: The Eurozone Crisis and the "Argentinean" Solution: Fuzzy Similarity and Default Risk (Jorge Pazzi, Fernando Tohme); A Discrete Particle Swarm Optimization Algorithm for Designing Electoral Zones (Eric A Rinc on-Garcia, Miguel A Gutierrez-Andrade, Sergio G de-los-Cobos-Silva, Pedro Lara-Velazquez, Roman A Mora-Gutierrez, Antonin S Ponsich); Locating enterprises using a fuzzy logic-based strategy (Gonzalez Santoyo Federico, Flores Romero Beatriz, Flores Romero Juan Jose); A Mathematical Model of Price Stabilization in Context of Uncertainty (Joan Bonet Amat, Joan Carles Ferrer Comalat, Elvira Cassu Serra, Salvador Linares Mustaros); An Stochastic Model of the Precautionary Principle (Maria Teresa Casparri, Javier Garcia Fronti); Management: An Analysis of the Quality Cost in a Business (Jose M Brotons Martinez, Manuel E Sansalvador Selles); Environmental Performance Measurement in Agri-Food Companies Using Fuzzy Inference System (Elena Escrig-Olmedo, Maria Jesus Munoz-Torres, Juana Maria Rivera-Lirio, Maria Angeles Fernandez-Izquierdo); Evaluation of the Quality of a Tourist Service Applied to the Case of Student Tourism (Luisa L Lazzari, Patricia Moulia, Andrea Parma); Fuzzy Analytic Hierarchy Process Approach for E-Commerce Websites Evaluation (Huan Liu, Viktor V Krasnoproshin, Shuang Zhang); Analysis of Industrial Cluster Agent Relations Using Fuzzy Subrelations (Antoni Vidal-Sune, Albert Fonts-Ribas); Neural Networks: Evolutionary Neural Network Classifiers for Monitoring Research, Development and Innovation Performance in European Union Member States (Monica de la Paz-Marin, Pilar Campoy-Munoz, Cesar Hervas-Martinez); Memory in Financial Time Series: From Investor Behavior to Artificial Neural Networks (M Teresa Sorrosal-Forradellas, M Gloria Barbera-Marine, Lisana B Martinez, Maria-Jose Garbajosa-Cabello); Capital Structure in the Spanish Chemical Industry. How Does the Financial Crisis Affect? (Xavier Camara-Turull, Xavier Borras Balsells, M Teresa Sorrosal-Forradellas, M Angeles Fernandez-Izquierdo); Using Neural Networks to Model Sovereign Credit Ratings: Application to the European Union (Raul Leon, Maria Jesus Munoz); The Effect of Changes of the Hurst Exponent in Return Predictability: The Case of the Dutch Market (Laura Lanzarini, Aurelio Fernandez Bariviera, M Belen Guercio, Cristina Tomas-Monterde); Knowledge Management and Innovation: Organizational Learning in Complex Environments: Exploration and Exploitation in a NK Landscape (Bocanet Anca, Iandoli Luca, Cristina Ponsiglione, Giuseppe Zollo); Variables Fostering Knowledge Management Classical Theory vs. Uncertainty Theory (Gerardo Gabriel Alfaro Calderon, Federico Gonzalez Santoyo, Juan J Flores, Victor Gerardo Alfaro Garcia); Multi-Objective Fuzzy Models in the Selection of Innovations in the Agricultural Area (Luis M Rivera Vilas, Natalia Lopez-Mosquera Garcia, Mercedes Sanchez Garciaxiv).
£135.00
World Scientific Publishing Co Pte Ltd Principles Of Artificial Neural Networks (3rd
Book SynopsisArtificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition — all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained.The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.Table of ContentsIntroduction and Role of Artificial Neural Networks; Fundamentals of Biological Neural Networks; Basic Principles of ANNs and Their Early Structures; The Perceptron; The Madaline; Back Propagation; Hopfield Networks; Counter Propagation; Large Scale Memory Storage and Retrieval (LAMSTAR) Network; Adaptive Resonance Theory; The Cognitron and the Neocognitron; Statistical Training; Recurrent (Time Cycling) Back Propagation Networks.
£108.00
World Scientific Publishing Co Pte Ltd Arithmetic Of Z-numbers, The: Theory And
Book SynopsisReal-world information is imperfect and is usually described in natural language (NL). Moreover, this information is often partially reliable and a degree of reliability is also expressed in NL. In view of this, the concept of a Z-number is a more adequate concept for the description of real-world information. The main critical problem that naturally arises in processing Z-numbers-based information is the computation with Z-numbers. Nowadays, there is no arithmetic of Z-numbers suggested in existing literature.This book is the first to present a comprehensive and self-contained theory of Z-arithmetic and its applications. Many of the concepts and techniques described in the book, with carefully worked-out examples, are original and appear in the literature for the first time.The book will be helpful for professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.Table of ContentsThe General Concept of a Restriction and Z-numbers; Definitions and Main Properties of Z-Numbers; Operations on Continuous Z-Numbers; Operations on Discrete Z-Numbers; Algebraic System of Z-Numbers; Z-Number Based Operation Research Problems; Application of Z-Numbers;
£94.50
World Scientific Publishing Company Advanced Randomized Neural Networks For Pattern Analysis
£108.00
Springer Verlag, Singapore Neural Information Processing: 29th International
Book SynopsisThe four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications.The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.Table of ContentsTheory and Algorithms.- Knowledge Transfer from Situation Evaluation to Multi-agent Reinforcement Learning.- Sequential three-way rules class-overlap under-sampling based on fuzzy hierarchical subspace for imbalanced data.- Two-stage Multilayer Perceptron Hawkes Process.- The Context Hierarchical Contrastive Learning for Time Series in Frequency Domain.- Hawkes Process via Graph Contrastive Discriminant representation Learning and Transformer capturing long-term dependencies.- A Temporal Consistency Enhancement Algorithm Based On Pixel Flicker Correction.- Data representation and clustering with double low-rank constraints.- RoMA: a Method for Neural Network Robustness Measurement and Assessment.- Independent Relationship Detection for Real-Time Scene Graph Generation.- A multi-label feature selection method based on feature graph with ridge regression and eigenvector centrality.- O3GPT: A Guidance-Oriented Periodic Testing Framework with Online Learning, Online Testing, and Online Feedback.- AFFSRN: Attention-Based Feature Fusion Super-Resolution Network.- Temporal-Sequential Learning with Columnar-Structured Spiking Neural Networks.- Graph Attention Transformer Network for Robust Visual Tracking.- GCL-KGE:Graph Contrastive Learning for Knowledge Graph Embedding.- Towards a Unified Benchmark for Reinforcement Learning in Sparse Reward Environments.- Effect of Logistic Activation Function and Multiplicative Input Noise on DNN-kWTA model.- A High-Speed SSVEP-Based Speller Using Continuous Spelling Method.- AAT: Non-Local Networks for Sim-to-Real Adversarial Augmentation Transfer.- Aggregating Intra-class and Inter-class information for Multi-label Text Classification.- Fast estimation of multidimensional regression functions by the Parzen kernel-based method.- ReGAE: Graph autoencoder based on recursive neural networks.- Efficient Uncertainty Quantification for Under-constraint Prediction following Learning using MCMC.- SMART: A Robustness Evaluation Framework for Neural Networks.- Time-aware Quaternion Convolutional Network for Temporal Knowledge Graph Reasoning.- SumBART - An improved BART model for abstractive text summarization.- Saliency-Guided Learned Image Compression for Object Detection.- Multi-Label Learning with Data Self-Augmentation.- MnRec: A News Recommendation Fusion Model Combining Multi-granularity Information.- Infinite Label Selection Method for Mutil-label Classification.- Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning.- Searching for Textual Adversarial Examples with Learned Strategy.- Multivariate Time Series Retrieval with Binary Coding from Transformer. -Learning TSP Combinatorial Search and Optimization with Heuristic Search.- A Joint Learning Model for Open Set Recognition with Post-processing.- Cross-Layer Fusion for Feature Distillation.- MCHPT: A Weakly Supervise Based Merchant Pre-trained Model.- Progressive Latent Replay for efficient Generative Rehearsal.- Generalization Bounds for Set-to-Set Matching with Negative Sampling.- ADA: An Attention-Based Data Augmentation Approach to Handle Imbalanced Textual Datasets.- Countering the Anti-detection Adversarial Attacks.- Evolving Temporal Knowledge Graphs by Iterative Spatio-Temporal Walks.- Improving Knowledge Graph Embedding Using Dynamic Aggregation of Neighbor Information.- Generative Generalized Zero-Shot Learning based on Auxiliary-Features.- Learning Stable Representations with Progressive Autoencoder (PAE).- Effect of Image Down-sampling on Detection of Adversarial Examples .- Boosting the Robustness of Neural Networks with M-PGD.- StatMix: Data augmentation method that relies on image statistics in federated learning.- Classification by Components Including Chow's Reject Option. -Community discovery algorithm based on improved deep sparse autoencoder.- Fairly Constricted Multi-Objective Particle Swarm Optimization.- Argument Classification with BERT plus Contextual, Structural and Syntactic Features as Text.- Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient.- Optimizing Knowledge Distillation Via Shallow Texture Knowledge Transfer.- Unsupervised Domain Adaptation Supplemented with Generated Images.- MAR2MIX: A Novel Model for Dynamic Problem in Multi-Agent Reinforcement Learning.- Adversarial Training with Knowledge Distillation Considering Intermediate Representations in CNNs.- Deep Contrastive Multi-view Subspace Clustering.
£85.49
Springer Verlag, Singapore Neural Information Processing: 30th International
Book SynopsisThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. Table of ContentsTheory and Algorithms.- Efficient Lightweight Network with Transformer-based Distillation for Micro-crack Detection of Solar Cells.- {MTLAN: Multi-Task Learning and Auxiliary Network for Enhanced Sentence Embedding.- Correlated Online k-Nearest Neighbors Regressor Chain for Online Multi-Output Regression.- Evolutionary Computation for Berth Allocation Problems: A Survey.- Cognitive Neurosciences.- Privacy-Preserving Travel Time Prediction for Internet of Vehicles: A Crowdsensing and Federated Learning Approach.- A Fine-Grained Domain Adaptation Method for Cross-Session Vigilance Estimation in SSVEP-Based BCI.- RMPE:Reducing Residual Membrane Potential Error for Enabling High-accuracy and Ultra-low-latency Spiking Neural Networks.- An improved target searching and imaging method for CSAR.- Block-Matching Multi-Pedestrian Tracking.- RPF3D: Range-Pillar Feature Deep Fusion 3D Detector for Autonomous Driving.- Traffic Signal Control Optimization Based on Deep Reinforcement Learning With Attention Mechanisms.- CMCI: A Robust Multimodal Fusion Method For Spiking Neural Networks.- A Weakly Supervised Deep Learning Model for Alzheimer's Disease Prognosis Using MRI and Incomplete Labels.- Two-Stream Spectral-Temporal Denoising Network for End-to-end Robust EEG-based Emotion Recognition.- Brain-inspired Binaural Sound Source Localization Method Based On Liquid State Machine.- A Causality-Based Interpretable Cognitive Diagnosis Model.- RoBrain: Towards Robust Brain-to-Image Reconstruction via Cross-Domain Contrastive Learning.- High-dimensional multi-objective PSO based on radial projection.- Link Prediction Based on the Sub-graphs Learning with Fused Features.- Naturalistic Emotion Recognition Using EEG and Eye Movements.- Task Scheduling With Improved Particle Swarm Optimization In Cloud Data Center.- Traffic Signal Optimization at T-shaped intersections Based on Deep Q Networks.- A Multi-task Framework for Solving Multimodal Multiobjective Optimization Problems.- Domain Generalized Object Detection with Triple Graph Reasoning Network.- RPUC: Semi-supervised 3D Biomedical Image Segmentation through Rectified Pyramid Unsupervised Consistency.- Cancellable iris recognition scheme based on inversion fusion and local ranking.- EWMIGCN: Emotional Weighting based Multimodal Interaction Graph Convolutional Networks for Personalized Prediction.- Neighborhood Learning for Artificial Bee Colony Algorithm: A Mini-survey.- Human Centred Computing.- Channel Attention Separable Convolution Network for Skin Lesion Segmentation.- A DNN-based Learning Framework for Continuous Movements Segmentation.- Neural-Symbolic Recommendation with Graph-Enhanced Information.- Contrastive Hierarchical Gating Networks for Rating Prediction.- Interactive Selection Recommendation Based on the Multi-Head Attention Graph Neural Network.- CM-TCN: Channel-aware Multi-scale Temporal Convolutional Networks For Speech Emotion Recognition.- FLDNet: A Foreground-Aware Network for Polyp Segmentation Leveraging Long-Distance Dependencies.- Domain-Invariant Task Optimization for Cross-domain Recommendation.- Ensemble of randomized neural network and boosted trees for eye tracking-based driver situation awareness recognition and interpretation.- Temporal Modeling Approach for Video Action Recognition Based on Vision-Language Models.- A Deep Learning Framework with Pruning RoI Proposal for Dental Caries Detection in Panoramic X-ray Images.- User stance aware network for rumor detection using semantic relation inference and temporal graph convolution.- IEEG-CT: A CNN and Transformer Based Method for Intracranial EEG Signal Classification.- Multi-Task Learning Network for Automatic Pancreatic Tumor Segmentation and Classification with Inter-Network Channel Feature Fusion.- Fast and Efficient Brain Extraction with Recursive MLP based 3D UNet.- A Hip-Knee Joint Coordination Evaluation System in Hemiplegic Individuals Based on Cyclogram Analysis.- Evaluation of football players' performance based on Multi-Criteria Decision Analysis approach and sensitivity analysis.
£75.99
Springer Verlag, Singapore Neural Information Processing: 30th International
Book SynopsisThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. Table of ContentsText to Image Generation with Conformer-GAN.- MGFNet: A Multi-Granularity Feature Fusion and Mining Network for Visible-Infrared Person Re-Identification.- Isomorphic Dual-Branch Network for Non-homogeneous Image Dehazing and Super-Resolution.- Hi-Stega : A Hierarchical Linguistic Steganography Framework Combining Retrieval and Generation.- Effi-Seg: Rethinking EfficientNet Architecture for Real-time Semantic Segmentation.- Quantum Autoencoder Frameworks for Network Anomaly Detection.- Spatially-Aware Human-Object Interaction Detection with Cross-Modal Enhancement.- Intelligent trajectory tracking control of unmanned parafoil system based on SAC optimized LADRC.- CATS: Connection-aware and Interaction-based Text Steganalysis in Social Networks.- Syntax Tree Constrained Graph Network for Visual Question Answering.- CKR-Calibrator: Convolution Kernel Robustness Evaluation and Calibration.- SGLP-Net: Sparse Graph Label Propagation Network for Weakly-Supervised Temporal Action Localization.- VFIQ: A Novel Model of ViT-FSIMc Hybrid Siamese Network for Image Quality Assessment.- Spiking Reinforcement Learning for Weakly-supervised Anomaly Detection.- Resource-aware DNN Partitioning for Privacy-sensitive Edge-Cloud Systems.- A frequency reconfigurable multi-mode printed antenna.- Multi-view Contrastive learning for Knowledge-aware Recommendation.- PYGC: a PinYin Language Model Guided Correction Model for Chinese Spell Checking.- Empirical Analysis of Multi-label Classification on GitterCom using BERT.- A lightweight safety helmet detection network based on bidirectional connection module and Polarized Self-Attention.- Direct Inter-Intra View Association for Light Field Super-Resolution.- Responsive CPG-Based Locomotion Control for Quadruped Robots.- Vessel Behavior Anomaly Detection using Graph Attention Network.- TASFormer: Task-aware Image Segmentation Transformer.- Unsupervised Joint-Semantics Autoencoder Hashing for Multimedia Retrieval.- TKGR-RHETNE：A New Temporal Knowledge Graph Reasoning Model via Jointly Modeling Relevant Historical Event and Temporal Neighborhood Event Context.- High-Resolution Self-Attention with Fair Loss for Point Cloud Segmentation.- Transformer-based Video Deinterlacing Method.- SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack.- CSEC: A Chinese Semantic Error Correction Dataset for Written Correction.- Contrastive Kernel Subspace Clustering.- UATR: An Uncertainty Aware Two-stage Refinement Model for Targeted Sentiment Analysis.- AttIN: Paying More Attention to Neighborhood Information for Entity Typing in Knowledge Graphs.- Text-based Person Re-ID by Saliency Mask and Dynamic Label Smoothing.- Robust Multi-view Spectral Clustering with Auto-encoder for Preserving Information.- Learnable Color Image Zero-Watermarking Based on Feature Comparison.- P-IoU: Accurate Motion Prediction based Data Association for Multi-Object Tracking.- WCA-VFnet:a dedicated complex forest smoke fire detector.- Label Selection Algorithm Based on Ant Colony Optimization and Reinforcement Learning for Multi-label Classification.- Reversible Data Hiding Based on Adaptive Embedding with Local Complexity.- Generalized Category Discovery with Clustering Assignment Consistency.- CInvISP: Conditional Invertible Image Signal Processing Pipeline.- Ignored Details in Eyes: Exposing GAN-generated Faces by Sclera.- A Developer Recommendation Method Based on Disentangled.- Graph Convolutional Network.- Novel Method for Radar Echo Target Detection.
£66.49
EPB Publishers Pte Ltd Neural Networks: Computers With Intuition
£27.55
Science eBook Comprendre le Deep Learning: Une introduction aux
Book Synopsis
£14.50
