Image processing Books

Book SynopsisThis four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.The papers are organized into the following topical sections: extracting document semantics, text and symbol recognition, document analysis systems, office automation, signature verification, document forensics and provenance analysis, pen-based document analysis, human document interaction, document synthesis, and graphs recognition.Table of ContentsExtracting Document Semantics.- MiikeMineStamps: A Long-Tailed Dataset of Japanese Stamps via Active Learning.- Deep Learning for Document Layout Generation: A First Reproducible Quantitative Evaluation and a Baseline Model.- Text and Symbol Recognition.- MRD: A Memory Relation Decoder for Online Handwritten Mathematical Expression Recognition.-Full Page Handwriting Recognition via Image to Sequence Extraction.- SPAN: a Simple Predict & Align Network for Handwritten Paragraph Recognition.- IHR-NomDB: The Old Degraded Vietnamese Handwritten Script Archive Database.- Sequence Learning Model for Syllables Recognition Arranged in Two Dimensions.- Transformer for Handwritten Text Recognition using Bidirectional Post-Decoding.- Zero-Shot Chinese Text Recognition via Matching Class Embedding.- Text-conditioned Character Segmentation for CTC-based Text Recognition.-Towards Fast, Accurate and Compact Online Handwritten Chinese Text Recognition.- HCADecoder: A Hybrid CTC-Attention Decoder for Chinese Text Recognition.-Meta-learning of Pooling Layers for Character Recognition.- Document Analysis Systems.- Text-line-up: Don’t Worry about the Caret.- Multimodal Attention-based Learning for Imbalanced Corporate Documents Classification.- Light-weight Document Image Cleanup using Perceptual Loss.- Office Automation.- A New Semi-Automatic Annotation Model via Semantic Boundary Estimation for Scene Text Detection.- Searching from the Prediction of Visual and Language Model for Handwritten Chinese Text Recognition.- Towards an IMU-based Pen Online Handwriting Recognizer.- Signature Verification.- 2D vs 3D online writer identification: a comparative study.- A Handwritten Signature Segmentation Approach for Multi-resolution and Complex Documents Acquired by Multiple Sources.- Attention based Multiple Siamese Network for Offline Signature Verification.- Attention to Warp: Deep Metric Learning for Multivariate Time Series.- Document Forensics and Provenance Analysis.- Customizable Camera Verification for Media Forensic.- Density Parameters of Handwriting in Schizophrenia and Affective Disorders Assessed Using the Raygraf Computer Software.- Pen-based Document Analysis.- Language-Independent Bimodal System for Early Parkinson’s Disease Detection.-TRACE: A Differentiable Approach to Line-level Stroke Recovery for Offline Handwritten Text.- Segmentation and graph matching for online analysis of student arithmetic operations.- Applying End-to-end Trainable Approach on Stroke Extraction in Handwritten Math Expressions Images.- A Novel Sigma-Lognormal Parameter Extractor for Online Signatures.- Human Document Interaction.- Near-perfect Relation Extraction from Family Books.- Estimating Human Legibility in Historic Manuscript Images - A Baseline.- A Modular and Automated Annotation Platform for Handwritings: Evaluation on Under-resourced Languages.- Reducing the Human Effort in Text Line Segmentation for Historical Documents.- DSCNN: Dimension Separable Convolutional Neural Networks for character recognition based on inertial sensor signal.- Document Synthesis.- DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis.- Font Style that Fits an Image -- Font Generation Based on Image Context.- Bayesian Hyperparameter optimization of Deep Neural Network algorithms based on Ant Colony optimization.- End-to-End Approach for Recognition of Historical Digit Strings.- Generating Synthetic Handwritten Historical Documents With OCR Constrained GANs.- Synthesizing Training Data for Handwritten Music Recognition.- Towards Book Cover Design via Layout Graphs.- Graphics Recognition.- Complete Optical Music Recognition via Agnostic Transcription and Machine Translation.- Improving Machine Understanding of Human Intent in Charts.- DeMatch: Towards Understanding the Panel of Chart Documents.- Sequential Next-Symbol Prediction for Optical Music Recognition.- Which Parts Determine the Impression of the Font?.- Impressions2Font: Generating Fonts by Specifying Impressions.

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Book SynopsisThis four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.The papers are organized into the following topical sections: scene text detection and recognition, document classification, gold-standard benchmarks and data sets, historical document analysis, and handwriting recognition. In addition, the volume contains results of 13 scientific competitions held during ICDAR 2021.Table of ContentsScene Text Detection and Recognition.- HRRegionNet: Chinese Character Segmentation in Historical Documents with Regional Awareness.- Fast Text v. Non-text Classification of Images.- Mask Scene Text Recognizer.- Rotated Box Is Back: An Accurate Box Proposal Network for Scene Text Detection.- Heterogeneous Network Based Semi-supervised Learning For Scene Text Recognition.- Scene Text Detection with Scribble Line.- EEM: An End-to-end Evaluation Metric for Scene Text Detection and Recognition.- SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models.- Fast Recognition for Multidirectional and Multi-Type License Plates with 2D Spatial Attention.- A Multi-level Progressive Rectification Mechanism for Irregular Scene Text Recognition.- Representation and Correlation Enhanced Encoder-Decoder Framework for Scene Text Recognition.- FEDS - Filtered Edit Distance Surrogate.- Bidirectional Regression for Arbitrary-Shaped Text Detection.- Document Classification.- VML-HP: Hebrew paleography dataset.- Open Set Authorship Attribution toward Demystifying Victorian Periodicals.- A More Effective Sentence-Wise Text Segmentation Approach using BERT.- Data Augmentation for Writer Identification Using a Cognitive Inspired Model.- Key-guided Identity Document Classification Method by Graph Attention Network.- Document Image Quality Assessment via Explicit Blur and Text Size Estimation.- Analyzing the potential of Zero-Shot Recognition for Document Image Classification.- Gender Detection Based on Spatial Pyramid Matching.- EDNets: Deep Feature Learning for Document Image Classification based on Multi-view Encoder-Decoder Neural Networks.- Fast End-to-end Deep Learning Identity Document Detection, Classification and Cropping.- Gold-Standard Benchmarks and Data Sets.- Image Collation: Matching illustrations in manuscripts.- Revisiting the Coco Panoptic Metric to Enable Visual and Qualitative Analysis of Historical Map Instance Segmentation.- A Large Multi-Target Dataset of Common Bengali Handwritten Graphemes.- GNHK: A Dataset for English Handwriting in the Wild.- Personalizing Handwriting Recognition Systems with Limited User-Specific Samples.- An Efficient Local Word Augment Approach for Mongolian Handwritten Script Recognition.- IIIT-INDIC-HW-WORDS: A Dataset for Indic Handwritten Text Recognition.- Historical Document Analysis.- AT-ST: Self-Training Adaptation Strategy for OCR in Domains with Limited Transcriptions.- TS-Net: OCR Trained to Switch Between Text Transcription Styles.- Handwriting Recognition with Novelty.- Vectorization of Historical Maps Using Deep Edge Filtering and Closed Shape Extraction.- Data Augmentation Based on CycleGAN for Improving Woodblock-printing Mongolian Words Recognition.- SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization.- Handwriting Recognition.- Recognizing Handwritten Chinese Texts with Insertion and Swapping Using A Structural Attention Network.- Strikethrough Removal From Handwritten Words Using CycleGANs.- Iterative Weighted Transductive Learning for Handwriting Recognition.- Competition Reports.- ICDAR 2021 Competition on Scientific Literature Parsing.- ICDAR 2021 Competition on Historical Document Classification.- ICDAR 2021 Competition on Document Visual Question Answering.- ICDAR 2021 Competition on Scene Video Text Spotting.- ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment.- ICDAR 2021 Competition on Components Segmentation Task of Document Photos.- ICDAR 2021 Competition on Historical Map Segmentation.- ICDAR 2021 Competition on Time-Quality Document Image Binarization.- ICDAR 2021 Competition on On-Line Signature Verification.- ICDAR 2021 Competition on Script Identification in the Wild.- ICDAR 2021 Competition on Scientific Table Image Recognition to LaTeX.- ICDAR 2021 Competition on Multimodal Emotion Recognition on Comics Scenes.- ICDAR 2021 Competition on Mathematical Formula Detection.

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Book SynopsisThis open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.Table of ContentsPart I - Introduction: 1. Digital Face Manipulation: An Introduction.- 2. Face Manipulation in Biometric Systems.- 3. Face Manipulation in Media Forensics.- Part II - Face Manipulation Detection Methods: 4. DeepFakes Manipulation.- 5. DeepFakes Detection.- 6. Attacking Face Recognition Systems with DeepFakes.- 7. Vulnerability of Face Recognition Systems to Morphing Attacks.- 8. Face Morphing Attack Detection.- 9. Face Synthesis Detection.- 10. Expression Swap Detection.- 11. Audio- and Text-to-Video Detection.- 12. Detection of Facial Retouching.- 13. Face De-Identification Detection.- Part III - Further Topics: 14. All-in-One Face Manipulation Detection: Generalization Analysis.- 15. Reversion of Face Manipulation.- 16. 3D Face Manipulation Detection.- 17. Improving Face Recognition with Face Image Manipulation.- 18. Impact of Post-Processing on Face Manipulation Detection.- 19. Societal and Legal Aspects of Face Manipulation.- 20. Face Manipulation for Privacy Protection.- 21. Privacy-preserving Face Manipulation Detection.- 22. Face Manipulation in Operational Systems.- Part IV - Open Issues, Trends, and Challenges: 23. All: Future trends in face Manipulation and Fake Detection.

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Book SynopsisThis book, geared towards both students and professionals, examines the synthesis of artificial intelligence (AI) and psychology in detecting mis-/disinformation in digital media content, and suggests practical means to intervene and curtail this current global ‘infodemic’. This interdisciplinary book explores technological, psychological, philosophical, and linguistic insights into the nature of truth and deception, trust and credibility, cognitive biases and logical fallacies and how, through AI and human intervention, content users can be alerted to the presence of deception. The author investigates how AI can mimic the procedures and know-hows of humans, showing how AI can help spot fakes and how AI tools can work to debunk rumors and fact-check. The book describes how AI detection systems work and how they fit with broader societal and individual concerns. Each chapter focuses attention on key concepts and their inter-connection. The first part of the book seeks theoretical footing to understand our interactions with new information and reviews relevant empirical findings in behavioral sciences. The second part is about applied knowledge. The author looks at several known practices that guard us against deception, and provides several real-world examples of manipulative persuasive techniques in advertising, political propaganda, and public relations. She provides links to the downloadable executable files to three AI applications (clickbait, satire, and falsehood detectors) via LiT.RL GitHub, an open access repository. The book is useful to students and professionals studying AI and media studies as well as library and information professionals. Examines how artificial intelligence (AI) and psychology can aid in detecting mis-/disinformation and the language of deceit in digital media content; Suggests practical computational means to intervene and curtail the global ‘infodemic’ of fake news; Presents how AI can sift, sort, and shuffle digital content, to reduce the amount of content needed to be reviewed by humans. Table of ContentsIntroduction.- Infodemic in the Digital Media Content.- Part I. Human Nature of Deception and Perceptions of Truth.- Psychology of Mis-/Disinformation and Language of Deceit.- Library and Information Science on Credibility and Trust in Computing.- Philosophies of Truth.- Part II. Applied Practices and Artificial Intelligence (AI).- Investigation in Law Enforcement, Journalism, and Sciences.- Manipulation in Marketing, Advertising, and Public Relations.- Artificially Intelligent Solutions: Detection, Debunking, Fact-Checking.- Lessons for Infodemic Control and Future of Digital Content Verification.- Conclusion.

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Book SynopsisThis book gathers outstanding research papers presented at the International Conference on Intelligent Vision and Computing (ICIVC 2021), held online during October 03–04, 2021. ICIVC 2021 is organised by Sur University, Oman. The book presents novel contributions in intelligent vision and computing and serves as reference material for beginners and advanced research. The topics covered are intelligent systems, intelligent data analytics and computing, intelligent vision and applications collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal natural language processing.Table of ContentsHandwritten Bengali Digit Classification using Deep Learning.- IOT Based COVID Patient Health Monitoring System In Quarantine.- Self-attention Convolution for Sparse to Dense Depth Completion.- Using Algorithm in Parametric Design as an Approach to Inspire Nature in Architectural Design.- Docker Container Orchestration Management in Cloud Computing.- Locally Weighted Mean Phase Angle (LWMPA) Based Tone Mapping Quality Index.

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Book SynopsisComputer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.Table of ContentsPreface.- Acknowledgments.- Introduction.- Features and Classifiers.- Neural Networks Basics.- Convolutional Neural Network.- CNN Learning.- Examples of CNN Architectures.- Applications of CNNs in Computer Vision.- Deep Learning Tools and Libraries.- Conclusion.- Bibliography.- Authors' Biographies.

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Book SynopsisThis two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.Table of ContentsEvolutionary Computing and Learning. Neural Networks.- Pattern Recognition.- Image Processing.- Information Security.- Biomedical Informatics Theory and Methods.- Biomedical Data Modeling and Mining.- Intelligent Computing in Computational Biology.- Computational Genomics and Biomarker Discovery.- Intelligent Computing in Drug Design.- Theoretical Computational Intelligence and Applications.- Fuzzy Theory and Algorithms.- Machine Learning and Data Mining.- Intelligent Computing in Computer Vision.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Intelligent Computing and Optimization.

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Book SynopsisThis two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.Table of ContentsEvolutionary Computing and Learning. Neural Networks.- Pattern Recognition.- Image Processing.- Information Security.- Biomedical Informatics Theory and Methods.- Biomedical Data Modeling and Mining.- Intelligent Computing in Computational Biology.- Computational Genomics and Biomarker Discovery.- Intelligent Computing in Drug Design.- Theoretical Computational Intelligence and Applications.- Fuzzy Theory and Algorithms.- Machine Learning and Data Mining.- Intelligent Computing in Computer Vision.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Intelligent Computing and Optimization.

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Book SynopsisThis two volume proceedings, LNCS 13445 and 13446, constitutes the refereed proceedings of the 9th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, XR Salento 2022, held in Lecce, Italy, July 6–8, 2022. Due to COVID-19 pandemic the conference was held as a hybrid conference.The 42 full and 16 short papers were carefully reviewed and selected from 84 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, applications in cultural heritage, in medicine, in education, and in industry.Table of ContentseXtended Reality for learning and training.- Mixed Reality Agents for Automated Mentoring Processes.- Asynchronous Manual Work in Mixed Reality Remote Collaboration.- A virtual reality serious game for children with dyslexia: DixGame.- Processing Physiological Sensor Data in Near Real-Time as Social Signals for their Use on Social Virtual Reality Platforms.- Developing a tutorial for improving usability and user skills in an immersive virtual reality experience.- Challenges in Virtual Reality Training for CRBN Events.- A Preliminary Study on the Teaching Mode of Interactive VR Painting Ability Cultivation.- eXtended Reality in education.- Factors in the cognitive-emotional impact of Educational Environmental Narrative Videogames.- Instinct-based Decision-making in Interactive Narratives.- The application of immersive virtual reality for children's road education: validation of a pedestrian crossing scenario.- Collaborative VR scene broadcasting for geometry education.- Collaborative Mixed Reality Annotations System for Science and History Education Based on UWB Positioning and Low-cost AR Glasses.- Artificial Intelligence and Machine Learning for eXtended Reality.- Can AI replace conventional markerless tracking? A comparative performance study for mobile augmented reality based on artificial intelligence..- Find, Fuse, Fight: genetic algorithms to provide engaging content for multiplayer augmented reality games.- Synthetic data generation for surface defect detection*.- eXtended Reality in Geo-Information Sciences.- ARtefact: A Conceptual Framework for the Integrated Information Management of Archaeological Excavations.- Geomatics meets XR: a brief overview of the synergy between Geospatial data and augmented visualization..- Utilization of Geographic Data for the Creation of Occlusion Models in the Context of Mixed Reality Applications.- Development of an open-source 3D WebGIS framework to promote cultural heritage dissemination.- Industrial eXtended Reality.- A FRAMEWORK FOR DEVELOPING XR APPLICATIONS INCLUDING MULTIPLE SENSORIAL MEDIA.- Augmented Reality Remote Maintenance in Industry: A Systematic Literature Review.- Virtual Teleoperation Setup for a Bimanual Bartending Robot.- eXtended Reality in the digital transformation of museums.- Virtualization and Vice Versa: A new procedural model of the reverse virtualization for the user behavior tracking in the Virtual Museums.- “You can tell a man by the emotion he feels”: How Emotions Influence Visual Inspection of Abstract Art in Immersive Virtual Reality.- Augmented Reality and 3D Printing for Archaeological Heritage: Evaluation of Visitor Experience.- Building blocks for multi-dimensional WebXR inspection tools targeting Cultural Heritage.- Comparing the impact of low-cost 360° cultural heritage videos displayed in 2D screens versus virtual reality headsets.- eXtended Reality beyond the five senses.- Non-immersive versus immersive extended reality for motor imagery neurofeedback within a brain-computer interfaces.- Virtual Reality enhances EEG-based neurofeedback for emotional self-regulation.- Psychological and Educational Interventions Among Cancer Patients: A Systematic Review to Analyze the Role of Immersive Virtual Reality for Improving Patients’ Well-Being.

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Book SynopsisThis book constitutes the refereed proceedings of the 19th International Conference on Virtual Reality and Mixed Reality, EuroXR 2022, held in Stuttgart, Germany, in September 2022.The 6 full and 2 short papers were carefully reviewed and selected from 37 submissions. The conference presents contributions on results and insights in Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), commonly referred to under the umbrella of Extended Reality (XR), including software systems, immersive rendering technologies, 3D user interfaces, and applications. Table of ContentsDesigning Functional Prototypes Combining BCI and AR for Home Automation.- SightX: A 3D Selection Technique for XR.- Design and Evaluation of Three User Interfaces for Detecting Unmanned Aerial Vehicles Using Virtual Reality.- Evaluating the Acceptability and Usability of a Head-Mounted Augmented Reality Approach for Autistic Children With High Support Needs.- Exploiting Augmented Reality in LEGO Therapy for Children with Autism Spectrum Disorder.- Evaluation of Point Cloud Streaming and Rendering for VR-based Telepresence in the OR.- Fast Intra-Frame Video Splicing for Occlusion Removal in Diminished Reality.- Coupling AR with object detection neural networks for end-user engagement.- A Procedural Building Generator based on Real-World Data Enabling Designers to Create Context for XR Automotive Design Experiences.- Generating VR meeting rooms with non-rectangular floor plans using cost optimization and hard constraints.- Controlling Continuous Locomotion in Virtual Reality With Bare Hands using Hand Gestures.- An Augmented Reality solution for the Positive Behaviour Intervention and Support.- The Reality of Virtual Experiences: Semantic and Epi-sodic Memory Formation in VR.

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Book SynopsisThe eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization; Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies. Table of ContentsBrain Development and Atlases.- Progression models for imaging data with Longitudinal Variational Auto Encoders.- Boundary-Enhanced Self-Supervised Learning for Brain Structure Segmentation.- Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline.- 3D Global Fourier Network for Alzheimer’s Disease Diagnosis using Structural MRI.- CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis.- Interpretable differential diagnosis for Alzheimer’s disease and Frontotemporal dementia.- Is a PET all you need? A multi-modal study for Alzheimer’s disease using 3D CNNs.- Unsupervised Representation Learning of Cingulate Cortical Folding Patterns.- Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer’s disease detection.- Extended Electrophysiological Source Imaging with Spatial Graph Filters.- DWI and Tractography.- Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data.- Atlas-powered deep learning (ADL) - application to diffusion weighted MRI.- One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation.- Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner.- An adaptive network with extragradient for diffusion MRI-based microstructure estimation.- Shape-based features of white matter fiber-tracts associated with outcome in Major Depression Disorder.- White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning.- Segmentation of Whole-brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points.- TractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers.- Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression.- Functional Brain Networks.- Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification.- Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome.- Decoding Task Sub-type States with Group Deep Bidirectional Recurrent Neural Network.- Hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network.- Interpretable signature of consciousness in resting-state functional network brain activity.- Nonlinear Conditional Time-varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels.- fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits.- Multi-head Attention-based Masked Sequence Model for Mapping Functional Brain Networks.- Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning.- RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis.- Modelling Cycles in Brain Networks with the Hodge Laplacian.- Predicting Spatio-Temporal Human Brain Response Using fMRI.- Revealing Continuous Brain Dynamical Organization with Multimodal Graph Transformer.- Explainable Contrastive Multiview Graph Representation of Brain, Mind, and Behavior.- Embedding Human Brain Function via Transformer.- How Much to Aggregate: Learning Adaptive Node-wise Scales on Graphs for Brain Networks.- Combining multiple atlases to estimate data-driven mappings between functional connectomes using optimal transport.- The Semi-constrained Network-Based Statistic (scNBS): integrating local and global information for brain network inference.- Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder.- Neuroimaging.- Characterization of brain activity patterns across states of consciousness based on variational auto-encoders.- Conditional VAEs for confound removal and normative modelling of neurodegenerative diseases.- Semi-supervised learning with data harmonisation for biomarker discovery from resting state fMRI.- Cerebral Microbleeds Detection Using a 3D Feature Fused Region Proposal Network with Hard Sample Prototype Learning.- Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer’s Disease.- Heart and Lung Imaging.- AANet: Artery-Aware Network for Pulmonary Embolism Detection in CTPA Images.- Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT Scans.- What Makes for Automatic Reconstruction of Pulmonary Segments.- CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs.- Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation.- Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision.- Diffusion Deformable Model for 4D Temporal Medical Image Generation.- SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-Sequence MRI Diagnosis.- Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification.- Detecting Aortic Valve Pathology from the 3-Chamber Cine Cardiac MRI View.- CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays.- Reinforcement learning for active modality selection during diagnosis.- Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings.- Attention mechanisms for physiological signal deep learning: which attention should we take?.- Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance.- Multimodal Contrastive Learning for Prospective Personalized Estimation of CT Organ Dose.- RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment.- A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000.- LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection.- Consistency-based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification.- Self-Rating Curriculum Learning for Localization and Segmentation of Tuberculosis on Chest Radiograph.- Rib Suppression in Digital Chest Tomosynthesis.- Multi-Task Lung Nodule Detection in Chest Radiographs with a Dual Head Network.- Dermatology.- Data-Driven Deep Supervision for Skin Lesion Classification.- Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images.- FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis.- Reliability-aware Contrastive Self-ensembling for Semi-supervised Medical Image Classification.

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Book SynopsisThe eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections:Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;Part III: Breast imaging; colonoscopy; computer aided diagnosis;Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;Part VI: Image registration; image reconstruction;Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization;Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies. Table of ContentsMachine learning – weakly-supervised learning.- machine learning – model interpretation.- machine learning – uncertainty.- machine learning theory and methodologies.

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Book SynopsisThis book constitutes the refereed proceedings of the first MICCAI Workshop on Resource-Efficient Medical Image Analysis, REMIA 2022, held in conjunction with MICCAI 2022, in September 2022 as a hybrid event. REMIA 2022 accepted 13 papers from the 19 submissions received. The workshop aims at creating a discussion on the issues for practical applications of medical imaging systems with data, label and hardware limitations.Table of ContentsMulti-Task Semi-Supervised Learning for Vascular Network.- Segmentation and Renal Cell Carcinoma Classification.- Self-supervised Antigen Detection Artificial Intelligence (SANDI).- RadTex: Learning Effcient Radiograph Representations from Text Reports.- Single Domain Generalization via Spontaneous Amplitude Spectrum Diversification.- Triple-View Feature Learning for Medical Image Segmentation.- Classification of 4D fMRI Images Using ML, Focusing on Computational and Memory Utilization Effciency.- An Effcient Defending Mechanism Against Image Attacking On Medical Image Segmentation Models.- Leverage Supervised and Self-supervised Pretrain Models for Pathological Survival Analysis via a Simple and Low-cost Joint Representation Tuning.- Pathological Image Contrastive Self-Supervised Learning.- Investigation of Training Multiple Instance Learning Networks with Instance Sampling.- Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound.- A self-attentive meta-learning approach for image-based few-shot disease detection.- Facing Annotation Redundancy: OCT Layer Segmentation with Only 10 Annotated Pixels Per Layer.

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Book SynopsisThis book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.Table of ContentsCellular Architecture on Whole Slide Images Allows the Prediction of Survival in Lung Adenocarcinoma .- Is More Always Better? Effects of Patch Sampling in Distinguishing Chronic Lymphocytic Leukemia from Transformation to Diffuse Large B-cell Lymphoma.- Repeatability of Radiomic Features against Simulated Scanning Position Stochasticity across Imaging Modalities and Cancer Subtypes: A Retrospective Multi-Institutional Study on Head-and-Neck Cases.- MLCN: Metric Learning Constrained Network for Whole Slide Image Classification with Bilinear Gated Attention Mechanism.- NucDETR: End-to-End Transformer for Nucleus Detection in Histopathology Images.- Self-supervised learning based on a pre-trained method for the subtype classification of spinal tumors.- CanDLE: Illuminating Biases in Transcriptomic Pan-Cancer Diagnosis.- Cross-Stream Interactions: Segmentation of Lung Adenocarcinoma Growth Patterns.- Modality-collaborative AI model Ensemble for Lung Cancer Early Diagnosis.- Clustering-based Multi-instance Learning Network for Whole Slide Image Classification.- Multi-task Learning-driven Volume and Slice Level Contrastive Learning for 3D Medical Image Classification.- Light Annotation Fine Segmentation: Histology Image Segmentation based on VGG Fusion with Global Normalisation CAM.- Tubular Structure-Aware Convolutional Neural Networks for Organ at Risks Segmentation in Cervical Cancer Radiotherapy.- Automatic Computer-aided Histopathologic Segmentation for Nasopharyngeal Carcinoma using Transformer Framework.- Accurate Breast Tumor Identification UsingComputational Ultrasound Image Features.

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Book SynopsisThe 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022.The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.Table of Contents​Image Processing and Low-level Vision.- Video Deraining via Temporal Discrepancy Learning.- Multi-priors Guided Dehazing Network Based on Knowledge Distillation.- DLMP-Net: a dynamic yet lightweight multi-pyramid network for crowd density estimation.- CHENet: Image to Image Chinese Handwriting Eraser.- Identidication method for rice pests with small sample size problem combining deep learning and metric learning.- Boundary-Aware Polyp Segmentation Network.- SUDANet:A Siamese UNet with Dense Attention Mechanism for Remote Sensing Image Change Detection.- A Local-Global Self-attention Interaction Network for RGB-D Cross-modal Person Re-identification.- A RAW Burst Super-Resolution Method with Enhanced Denoising.- Unpaired and Self-supervised Optical Coherence Tomography Angiography Super-resolution.- Multi-Feature Fusion Network for Single Image Dehazing.- LAGAN: Landmark Aided Text to Face Sketch Generation.- DMF-CL: Dense Multi-scale Feature Contrastive Learning for Semantic segmentation of Remote-sensing images.- Image derain method for generative adversarial network based on wavelet high frequency feature fusion.- GPU-Accelerated Infrared Patch-Image Model for Small Target Detection.- Hyperspectral and Multispectral Image Fusion Based on Unsupervised Feature Mixing and Reconstruction Network.- Information Adversarial Disentanglement for Face Swapping.- A Dense Prediction ViT Network for Single Image Bokeh Rendering.- Multi-scale Coarse-to-fine Network for Demoiring.- Learning Contextual Embedding Deep Networks for Accurate and Efficient Image Deraining.- A Stage-Mutual-Ane Network for Single Remote Sensing Image Super-Resolution.- Style-based Attentive Network for Real-World Face Hallucination.- Cascade Scale-aware Distillation Network for Lightweight RemoteSensing Image Super-Resolution.- Few-Shot Segmentation via Rich Prototype Generation and RecurrentPrediction Enhancement.- Object Detection, Segmentation and Tracking.- TAFDet: A Task Awareness Focal Detector for Ship Detection in SAR Images.- MSDNet:Multi-scale Dense Networks for Salient Object Detection.- WaveSNet: Wavelet Integrated Deep Networks for Image Segmentation.- Infrared Object Detection Algorithm Based on Spatial Feature Enhancement.- Object Detection Based on Embedding Internal and External Knowledge.- ComLoss: A Novel Loss towards More Compact Predictions for Pedestrian Detection.- Remote sensing image detection based on attention mechanism and YOLOv5.- Detection of Pin Defects in Transmission Lines Based on Dynamic Receptive Field.- Identification of bird s nest hazard level of transmission line based on improved yolov5 and location constraints.- Image Magnification Network for Vessel Segmentation in OCTA Images.- CFA-Net: Cross-level Feature Fusion and Aggregation Network for Salient Object Detection.- Disentangled Feature Learning for Semi-supervised Person Re-identification.- Detection Beyond What and Where: A Benchmark for Detecting Occlusion State.- Weakly Supervised Object Localization with Noisy-Label Learning.- Enhanced Spatial Awareness For Deep Interactive Image Segmentation.- Anchor-Free Location Refinement Network for Small License Plate Detection.- Multi-View LiDAR Guided Monocular 3D Object Detection.- Dual Attention-guided Network for Anchor-free Apple Instance Segmentation in Complex Environments.- Attention-Aware Feature Distillation for Object Detection in Decompressed Images.- Cross-Stage Class-Specific Attention for Image Semantic Segmentation.- Defect Detection for High Voltage Transmission Lines Based on Deep Learning.- ORION: Orientation-Sensitive Object Detection.- An Infrared Moving Small Object Detection Method Based on Trajectory Growth.- Two-stage Object Tracking Based on Similarity Measurement for FusedFeatures of Positive and Negative Samples.- PolyTracker: Progressive Contour Regression for Multiple ObjectTracking and Segmentation.- Dual-branch Memory Network for Visual Object Tracking.- Instance-wise Contrastive Learning for Multi-Object Tracking.- Information Lossless Multi-Modal Image Generation for RGB-T Tracking.- JFT: A Robust Visual Tracker Based on Jitter Factor and Global Registration.- Caged Monkey Dataset: A New Benchmark for Caged Monkey Pose Estimation.- WTB-LLL: A Watercraft Tracking Benchmark Derived by Low-light-level Camera.- Dualray: Dual-view X-ray Security Inspection Benchmark and FusionDetection Framework.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2022, held in Kingsville, TX, USA, in collaboration with the Applied AI Research Laboratory of the University of South Dakota, during December 01-02, 2022.The 31 full papers included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: healthcare: medical imaging and informatics; computer vision and pattern recognition; internet of things and security; and signal processing and machine learning.Table of Contents​Healthcare: medical imaging and informatics.- Data Characterization for Reliable AI in Medicine.- Alzheimer’s Disease Detection using Ensemble Learning and Artificial Neural Networks.- Semi-supervised Multi-domain Learning for Medical Image Classification.- Significant CC400 functional brain parcellations based LeNet5 Convolutional Neural Network for Autism Spectrum Disorder detection.- 2D respiratory sound analysis to detect lung abnormalities.- Analyzing Chest X-Ray to Detect the Evidence of Lung Abnormality due to Infectious Disease.- Chest X-ray Image Super-resolution via Deep Contrast Consistent Feature Network.- A Novel Approach to Enhance Effectiveness of Image Segmentation Techniques on Extremely Noisy Medical Images.- Federated Learning for Lung Sound Analysis.- Performance Analysis of CNN and Quantized CNN Model for Rheumatoid Arthritis Identification using Thermal Image.- Image Processing and Pattern Recognition of Micropores of Polysulfone Membrane for the Bio-separation of Viruses from Whole Blood.- An Extreme Learning Machine-basedAutoEncoder (ELM-AE)for denoising knee X-ray images and grading knee osteoarthritis severity.- Computer Vision and Pattern Recognition.- Motor Imagery Classification CombiningRiemannian Geometry and Artificial Neural Networks.- Autism Spectrum Disorder Detection using Transfer Learning with VGG 19, Inception V3 and DenseNet 201.- Shrimp Shape Analysis by a Chord LengthFunction Based Methodology.- Supervised Neural Networks for Fruit Identification.- Targeted Clean-Label Poisoning Attacks On Federated Learning.- Building Marathi SentiWordNet.- A computational study on calibrated VGG19 formultimodal learning and representation insurveillance.- Automated Deep Learning based approach for Albinism Detection.- A Deep learning-based regression scheme for angle estimation in image dataset.- The classification of Native and Invasive Speciesin North America: A Transfer Learning and Random Forest Pipeline.- Internet of Things and Security.- Towards a Digital Twin Integrated DLT and IoT-based Automated Healthcare Ecosystem.- Enabling Edge Devices using Federated Learning and Big Data for Proactive Decisions.- IoT and Blockchain oriented gender determination of Bangladeshi populations.- Federated Learning based secured computational offloading in cyber-physical IoST systems.- A Hybrid Campus Security System Combined ofFace, Number-plate, and Voice Recognition.- Signal Processing and Machine.- Single-trial detection of event-related potentials with artificial examples based on coloring transformation.- Identifying the relationship between hypothesis and premise.- Data Poisoning Attack by Label Flipping onSplitFed Learning.- A Deep Learning-powered voice-enabled mathtutor for kids.

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Book SynopsisThe 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online.The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge.

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Book SynopsisThis three-volume set, LNCS 13421, 13422 and 13423, constitutes the thoroughly refereed proceedings of the 6th International Joint Conference, APWeb-WAIM 2022, held in Nanjing, China, in August 2022.The 75 full papers presented together with 45 short papers, and 5 demonstration papers were carefully reviewed and selected from 297 submissions. The papers are organized around the following topics: Big Data Analytic and Management, Advanced database and web applications, Cloud Computing and Crowdsourcing, Data Mining, Graph Data and Social Networks, Information Extraction and Retrieval, Knowledge Graph, Machine Learning, Query processing and optimization, Recommender Systems, Security, privacy, and trust and Blockchain data management and applications, and Spatial and multi-media data.Table of ContentsResearch tracks. Big Data Analytic and Management.- Advanced database and web applications.- Cloud Computing and Crowdsourcing.- Data Mining.- Graph Data and Social Networks.- Information Extraction and Retrieval.- Knowledge Graph.- Machine Learning.- Query processing and optimization.- Recommender Systems.- Security, privacy, and trust& Blockchain data management and applications.- Spatial and multi-media data.- Demo papers.

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Book SynopsisThe 7-volume set of LNCS 13841-13847 constitutes the proceedings of the 16th Asian Conference on Computer Vision, ACCV 2022, held in Macao, China, December 2022. The total of 277 contributions included in the proceedings set was carefully reviewed and selected from 836 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; optimization methods; Part II: applications of computer vision, vision for X; computational photography, sensing, and display; Part III: low-level vision, image processing; Part IV: face and gesture; pose and action; video analysis and event recognition; vision and language; biometrics; Part V: recognition: feature detection, indexing, matching, and shape representation; datasets and performance analysis; Part VI: biomedical image analysis; deep learning for computer vision; Part VII: generative models for computer vision; segmentation and grouping; motion and tracking; document image analysis; big data, large scale methods.

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Book SynopsisThis book constitutes the Third Diabetic Foot Ulcers Grand Challenge, DFUC 2022, which was held on September 2022, in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022 in Singapore. The 8 full papers presented together with 5 challenge papers and 3 post-challenge papers included in this book were carefully reviewed and selected from 19 submissions.The DFU challenges aim to motivate the health care domain to share datasets, participate in ground truth annotation, and enable data-innovation in computer algorithm development. In the longer term, it will lead to improved patient care.Table of ContentsQuantifying the Effect of Image Similarity on Diabetic Foot Ulcer Classification.- DFUC2022 Challenge Papers.- HarDNet-DFUS: Enhancing Backbone and Decoder of HarDNet-MSEGfor Diabetic Foot Ulcer Image Segmentation.- OCRNet For Diabetic Foot Ulcer Segmentation Combined with Edge Loss 30.- On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness.- Capture the Devil in the Details via Partition-then-Ensemble on Higher Resolution Images.- Unconditionally Generated and Pseudo-Labeled Synthetic Images for Diabetic Foot Ulcer Segmentation Dataset Extension.-Post Challenge Paper.- Diabetic Foot Ulcer Segmentation Using Convolutional and Transformer-based Refined Mixup Augmentation for Diabetic Foot Ulcer Segmentation.- Organization IX DFU-Ens: End-to-End Diabetic Foot Ulcer Segmentation Framework with Vision Transformer Based Detection.- Summary Paper.- Diabetic Foot Ulcer Grand Challenge 2022 Summary.

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Book SynopsisThe three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration papers, 12 reproducibility papers consortium papers, 7 tutorial papers, and 10 doctorial consortium papers were carefully reviewed and selected from 489 submissions. The book also contains, 8 workshop summaries and 13 CLEF Lab descriptions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.Table of ContentsReproducibility Papers.- Knowledge is Power, Understanding is Impact: Utility and Beyond Goals, Explanation Quality, and Fairness in Path Reasoning Recommendation.- Stat-weight: Improving the Estimator of Interleaved Methods Outcomes with Statistical Hypothesis Testing.- A Reproducibility Study of Question Retrieval for Clarifying Questions.- The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot Transfer.- Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study.- Index-Based Batch Query Processing Revisited.- A Unified Framework for Learned Sparse Retrieval.- Entity Embeddings for Entity Ranking: A Replicability Study.- Do the Findings of Document and Passage Retrieval Generalize to the Retrieval of Responses for Dialogues?.- PyGaggle: A Gaggle of Resources for Open-Domain Question Answering.- Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.- From Baseline to Top Performer: A Reproducibility Study of Approaches at the TREC 2021 Conversational Assistance Track.- Demonstration Papers.- Exploring Tabular Data Through Networks.- InfEval: Application for Object Detection Analysis.- The System for Efficient Indexing and Search in the Large Archives of Scanned Historical Documents.- Public News Archive: A Searchable Sub-Archive to Portuguese Past News Articles.- TweetStream2Story: Narrative Extraction from Tweets in Real Time.- SimpleRad: patient-friendly Dutch radiology reports.- Automated Extraction of Fine-Grained Standardized Product Information from Unstructured Multilingual Web Data.- Continuous Integration for Reproducible Shared Tasks with TIRA.io.- Dynamic Exploratory Search for the Information Retrieval Anthology.- Text2Storyline: Generating Enriched Storylines From Text.- Uptrendz: API-Centric Real-Time Recommendations in Multi-Domain Settings.- Clustering Without Knowing How To: Application and Evaluation.- Enticing local governments to produce FAIR freedom of information act dossiers.- Which Country is this? Automatic Country Ranking of StreetView Images.- Automatic Videography Generation from Audio Tracks.- Ablesbarkeitsmesser: A System for Assessing the Readability of German Text.- FACADE: Fake Articles Classification And Decision Explanation.- PsyProf: A Platform for Assisted Screening of Depression in Social Media.- SOPalign: A Tool for Automatic Estimation of Compliance with Medical Guidelines.- Tutorials.- Understanding and Mitigating Gender Bias in Information Retrieval Systems.- Neuro-Symbolic Representations for Information Retrieval.- Legal IR and NLP: the History, Challenges, and State-of-the-Art.- Deep Learning Methods for Query Auto Completion.- Trends and Overview: The Potential of Conversational Agents in Digital Health.- Crowdsourcing for Information Retrieval.- Uncertainty Quantification for Text Classification.- Workshops.- Fourth International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2023).- The 6th International Workshop on Narrative Extraction from Texts (Text2Story’23).- 2nd Workshop on Augmented Intelligence in Technology-Assisted Review Systems (ALTARS): Evaluation Metrics and Protocols for eDiscovery and Systematic Review Systems.- Workshop QPP++ 2023: Query Performance Prediction and Ist Evaluation in New Tasks.- Bibliometric-enhanced Information Retrieval: 13th International BIR Workshop (BIR˜2023).- Geographic information extraction from texts (GeoExT).- ROMCIR 2023: Overview of the 3rd Workshop on Reducing Online Misinformation through Credible Information Retrieval.- ECIR 2023 workshop proposal: Legal Information Retrieval.- Doctoral Consoritum.- Building Safe and Reliable AI systems for Safety Critical Tasks with Vision-Language Processing.- Text Information Retrieval in Tetun.- Identifying and Representing Knowledge Delta in Scientific Literature.- Investigation of Bias in Web Search Queries.- Monitoring online discussions and responses to support the identification of misinformation.- User Privacy in Recommender Systems.- Conversational Search for Multimedia Archives.- Disinformation Detection: Knowledge Infusion with Transfer Learning and Visualizations.- A Comprehensive Overview of Consumer Conflicts on Social Media.- Designing useful conversational interfaces for information retrieval in career decision-making support.- CLEF Lab Descriptions iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge.- LongEval: Longitudinal Evaluation of Model Performance at CLEF 2023.- The CLEF-2023 CheckThat! Lab: Checkworthiness, Subjectivity, Political Bias, Factuality, and Authority.- Overview of PAN 2023: Authorship Verification, Multi-Author Writing Style Analysis, Profiling Cryptocurrency Influencers, and Trigger Detection.- Overview of Touché 2023: Argument and Causal Retrieval.- CLEF 2023 SimpleText Track: What Happens if General Users Search Scientific Texts?.- Science for Fun: The CLEF 2023 JOKER Track on Automatic Wordplay Analysis.- ImageCLEF 2023 Highlight: Multimedia Retrieval in Medical, Social Media and Content Recommendation Applications.- LifeCLEF 2023 teaser: Species Identification and Prediction Challenges.- BioASQ at CLEF2023: The eleventh edition of the Large-scale biomedical semantic indexing and question answering challenge.- eRisk 2023: Depression, Pathological Gambling, and Eating Disorder Challenges.- Overview of EXIST 2023: sEXism Identification in Social neTworks.- DocILE 2023 Teaser: Document Information Localization and Extraction.

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Book SynopsisThe two-volume set LNAI 13495 and LNAI 13496, constitute the refereed post-workshop proceedings of the 23rd Chinese Lexical Semantics Workshop, CLSW 2022, held as a virtual event, during May 14-15, 2022. In total the two-volume set includes 39 full papers and 19 short papers which were carefully reviewed and selected from 214 submissions. They are organized in the following topical sections: lexical semantics; corpus linguistics; general linguistics, lexical resources; computational linguistics, applications of natural language processing.Table of ContentsSemantic Prosody: The Study of Gei in BA and BEI Constructions.- Corpus-Based Lexical Features and Thematic Analysis of China's Five-Year Plan for the 21st Century.- Corpus Construction for Generating Knowledge Graph of Sichuan Cuisine.- Building a Semantically Annotated Corpus of Chinese Directional Complements.- BBAE: a Method for Few-Shot Charge Prediction with Data Augmentation and Neural Network.- A Preliminary Quantitative Investigation of Chinese Monosyndetic Coordinators.- Frequency in Chinese Ballad Song Lyrics: A Quantitative Morpheme-Based Study.- Gender-Related Use of Tonal Patterns in Mandarin Chinese: The Case of Sentence-Final Particle ma.- A Quantitative Study on the Low-Degree Adverb “Shaowei”--A Stylistic Perspective.- The Relationship of Lexical Richness to the Quality of CSL Writings.- Research on Korean "Long-before-Short" Preference from the Perspective of Dependency Distance.- A Dependency Structure Annotation for Modality in Chinese News Articles.- How Do People React to COVID-19 Vaccination? A Corpus-based Study of Macau Netizens’ Online Comments.- REFORM IS A JOURNEY: Conceptualizing China’s Reform and Opening-up in the Official News Discourse.- The Emotion Code in Sensory Modalities: An investigation of the relationship between sensorimotor dimensions and emotional valence-arousal.- From Genitive to Conjunctive: Coordinator li55 in Chongqing Mandarin.- The Prediction Function of Collocations on the Quality Assessment of Chinese Second Language Learners’ Oral Production.- Verb Raising and the Construction Mechanism of Synthetic Compounds.- The Construction of Grammatical Synonym Resources of Disyllabic Verbs in Modern Chinese.- Extraction and Application of Verb Event Structure Based on Grammatical Knowledge-Base of Contemporary Chinese(GKB).- Semantic Classification of Adverbial Nouns Based on Syntactic Treebank and Construction of Collocation Da-tabase.- A Framework for Dictionary Development: Building Domain Dictionary for Legal Field.- RoBERTa: An Efficient Dating Method of Ancient Chinese Texts.- Building a Corpus for Chinese Causality Extraction in Futures Domain.- Research on Hotspots of Educational Application of Natural Language Processing Based on LDA Topic Model.- A Metrological Study on the Spatial Narrative of the Qishu Genre: Take A Dream of Red Mansions and Water Margin as Examples.- Chinese Argument Identification Based on Bert.- Irony Recognition in Chinese Text Based on Linguistic Features and Attention Mechanism.- A Phrase Disambiguation Method of “Quanbu V de N” Based on SBERT Model and Syntactic Rule.- Automatic Recognition of Verb-complement Separable Words Based on BCC.

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Book SynopsisThis book constitutes the proceedings of the Second International Conference on Information Technologies and Intelligent Decision Making Systems, ITIDMS 2022, held as a virtual event, December 12–14, 2022.The 14 papers presented in this volume were carefully reviewed and selected from 38 submissions. The conference was held with the aim of developing and exchanging international experience in the field of information, digital and intellectual technologies, within the framework of which proposals were formulated for digital, intellectual and infor-mation transformation, the development of computer models and the improvement of automated and computing processes. A distinctive feature of the conference is that it presented reports of authors from USA, Canada, Bangladesh, Uzbekistan and Russia. Researchers from different countries presented the process of transition of the information and digital path of development, presented the main directions and de-velopments that can improve the efficiency and development.Table of ContentsAlgorithm for Solving the Problem of Multi-Criteria Optimization of Poorly Formed Processes based on the Construction of a Fuzzy Logic Model.- PACTDet - An Artificially Intelligent Approach to Detect Pulmonary Illnesses: Pneumonia, Asthma, COVID-19, and Tuberculosis.- Detection of Video Image Modification using a Classifier based on Adaptive Resonance Theory.- On the Reduction of Alternatives in the Process of Selecting Preferred Management Decisions.- Performance Analysis of Machine Learning Algorithm on Cloud Platforms: AWS vs Azure vs GCP.- Mathematical Modeling of the Translation Process and its Optimization by the Criterion of Quality Maximization.- Optimization with Quantum Algorithm that is based on Grover’s Method.- Evaluation of the Efficiency of Fault Tolerance Algorithms for Distributed Peer-to-Peer Worker Processes Connected through a Key-Value Store.- Investigation of the Possibility of using Neural Networks to Predict the Concentration of Sodium in a Steam.- Using Ensemble Machine Learning Methods for Regional Forecasting of Geocryological Manifestations (on the Example of the European North-East of Russia).- Deghosting Diffusion Model for Facial Attribute Editing via Differential Activations.- Minimizing Defaultation in Lending Using Blockchain Based Loan Management Syste.- System of Intelligent-Safe Distribution of Network Traffic Loads in Cluster Mesh-Formations of Thermal Technology Systems.- Computer Research and Stabilization of Dynamic Models of Conveyor Systems.

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Book SynopsisThis book constitutes the refereed proceedings of the 28th International Conference on Applications of Natural Language to Information Systems, NLDB 2023, held in Derby, UK, in June 21–23, 2023The 31 full papers and 14 short papers included in this book were carefully reviewed and selected from 89 submissions. They focus on the developments of the application of natural language to databases and information systems in the wider meaning of the term.Table of ContentsLarge Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification.- How Challenging is Multimodal Irony Detection?.- Less is more: A Prototypical Framework for Efficient Few-Shot Named Entity Recognition.- Don’t Lose the Message while Paraphrasing: A Study on Content Preserving Style Transfer.- A Review of Parallel Corpora for Automatic Text Simplification. Key Challenges Moving Forward.- Explaining a Deep Learning Model for Aspect-Based Sentiment Classification Using Post-hoc Local Classifiers.- Arabic Privacy Policy Corpus and Classification.- SmartEDU: Accelerating Slide Deck Production with Natural Language Processing.- Explainable Integration of Knowledge Graphs using Large Language Models.- Cross-domain and cross-language irony detection: The impact of bias on models’ generalization.- Prompt and Instruction-Based Tuning for Response Generation in Conversational Question Answering.- IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.- Comparing object recognition models and studying hyperparameter selection for the detection of bolts.- Morphosyntactic Evaluation for Text Summarization in Morphologically Rich Languages: A Case Study for Turkish.- Building Knowledge Graphs in Heliophysics and Astrophysics.- Text to Image Synthesis Using Bridge Generative Adversarial Network and Char CNN Model.- Evaluation of transformer-based models for punctuation and capitalization restoration in Spanish and Portuguese.- Sentence-to-Label Generation Framework for Multi-task Learning of Japanese Sentence Classification and Named Entity Recognition.- Could KeyWord Masking strategy improve language model?.- Regularization, Semi-supervision, and Supervision for a Plausible Attention-Based Explanation.- Node-Weighted Centrality Ranking for Unsupervised Long Document Summarization.- Characterization of the city of the future from a science fiction corpus.- On the Rule-based Extraction of Statistics Reported in Scientific Papers.- GRAM: Grammar-Based Refined-Label Representing Mechanism in the Hierarchical Semantic Parsing Task.- Expanding Domain-specific Knowledge Graphs with Unknown Facts .- Knowledge Graph Representation Learning via Generated Descriptions.- LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts.- A Comparative Study of Evaluation Metrics for Long-Document Financial Narrative Summarization with Transformers.- Effective Information Retrieval, Question Answering and Abstractive Summarization on Large-scale Biomedical Document Corpora.- Abstractive Summarization Based Question-Answer System for Structural Information.- Adversarial Capsule Networks for Romanian Satire Detection and Sentiment Analysis.- A Few-shot Approach to Resume Information Extraction via Prompts.- Decoding Strategies for Code Conciseness and Efficiency in Transformer-Generated Programs.- SP-BERT: A Language Model for Political Text in Scandinavian Languages.- Improving Context-Awareness on Multi-Turn Dialogue Modeling with Extractive Summarization Techniques.- Document Knowledge Transfer for Aspect-Based Sentiment Classification Using a Left-Center-Right Separated Neural Network with Rotatory Attention.- Argument and counter-argument generation: a critical survey.- Novel Benchmark Data Set for Automatic Error Detection and Correction.- Weakly-Supervised Multimodal Learning for Predicting the Gender of Twitter Users.- Cross-Domain Toxic Spans Detection.- How shall a machine call a thing?.- Detecting Artificially Generated Academic Text: the Importance of Mimicking Human Utilization of Large Language Models.- Leveraging Small-BERT and Bio-BERT for Abbreviation Identification in Scientific Text.- RoBERTweet: A BERT Language Model for Romanian Tweets.- Evaluating the Effect of Letter Case on Named Entity Recognition Performance.

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Book SynopsisThis book investigates the image watermarking domain, analyzing and comparing image watermarking techniques that exist in current literature. The author’s goal is to aid researchers and students in their studies in the vast and important domain of image watermarking, including its advantages and risks. The book has three chapters: image watermarking using data compression; speech modulation for image watermarking; and secure image watermarking based on LWT and SVD.In addition, this book: Investigates the image watermarking domain, analyzing and comparing current image watermarking techniques Includes detail on image encryption and mathematical tools used for image watermarking Covers image watermarking using data compression, speech modulation for image watermarking, and more Table of ContentsIntroduction.- Image watermarking using data compression.- Speech modulation for image watermarking.- Secure Image Watermarking Based on LWT and SVD.- Speech Signal Embedding into Digital Images Using Encryption and Watermarking Techniques.- Conclusion.

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Book SynopsisThis two-volume set LNCS 14193-14194 constitutes the proceedings of International Workshops co-located with the 17th International Conference on Document Analysis and Recognition, ICDAR 2023, held in San José, CA, USA, during August 21–26, 2023. The total of 43 regular papers presented in this book were carefully selected from 60 submissions. Part I contains 22 regular papers that stem from the following workshops: ICDAR 2023 Workshop on Computational Paleography (IWCP); ICDAR 2023 Workshop on Camera-Based Document Analysis and Recognition (CBDAR); ICDAR 2023 International Workshop on Graphics Recognition (GREC); ICDAR 2023 Workshop on Automatically Domain-Adapted and Personalized Document Analysis (ADAPDA); Part II contains 21 regular papers that stem from the following workshops: ICDAR 2023 Workshop on Machine Vision and NLP for Document Analysis (VINALDO); ICDAR 2023 International Workshop on Machine Learning (WML). Table of ContentsTypefaces and Ligatures in Printed Arabic Text: A Deep Learning-Based OCR Perspective.- Leveraging Knowledge Graph Embeddings to Enhance Contextual Representations for Relation Extraction.- Extracting Key-Value Pairs in Business Documents.- Long-Range Transformer Architectures for Document Understanding.-Pre-training transformers for Corporate Documents Understanding.- Transformer-Based Neural Machine Translation for Post-OCR Error Correction in Cursive Text.- Arxiv Tables: Document Understanding Challenge Linking Texts and Tables.- Subgraph-Induced Extraction Technique for Information (SETI) from Administrative Documents.- Document Layout Annotation: Database and Benchmark in the Domain of Public Affairs.- A Clustering Approach Combining Lines and Text Detection for Table Extraction.- Absformer: Transformer-Based Model for Unsupervised Multi-Document Abstractive Summarization.- A Comparison of Demographic Attributes Detection from Handwriting Based on Traditional and Deep Learning Methods.- A New Optimization Approach to Improve an Ensemble Learning Model: Application to Persian/Arabic Handwritten Character Recognition.- BN-DRISHTI: Bangla Document Recognition Through Instance-level Segmentation of Handwritten Text Images.- Text Line Detection and Recognition of Greek Polytonic Documents.- A Comprehensive Handwritten Paragraph Text Recognition System: LexiconNet.- Local Style Awareness of Font Images.- Fourier Feature-Based CBAM and Vision Transformer for Text Detection in Drone Images.- Document Binarization with Quaternionic Double Discriminator Generative Adversarial Network.- Crosslingual Handwritten Text Generation Using GANs.- Knowledge Integration inside Multitask Network for Analysis of Unseen ID Types.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. For this workshop, 21 papers from 32 submissions were accepted for publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.Table of ContentsUncertainty estimation and modelling.- Out of Distribution management and domain shift robustness.- Bayesian deep learning and uncertainty calibration.

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Book SynopsisThis book constitutes the proceedings of the 4th International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2023, held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Vancouver, BC, Canada, on October 8, 2023. The 19 papers presented in this book were carefully reviewed and selected from 30 submissions. They were organized in topical sections as follows:​ advanced imaging, segmentation, and ultrasound techniques; predictive analysis, learning, and classification; multimodal imaging, reconstruction, and real-time applications; diagnostic enhancements and novel ultrasound innovations.Table of ContentsAdvanced Imaging, Segmentation, and Ultrasound Techniques.- Predictive Analysis, Learning, and Classification.- Multimodal Imaging, Reconstruction, and Real-time Applications.- Diagnostic Enhancements and Novel Ultrasound Innovations.

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Book SynopsisThis book constitutes the refereed proceedings of the 9th Joint International Conference on Serious Games, JCSG 2023, held in Dublin, Ireland, during October 26–27, 2023. The 18 full papers presented together with 9 short papers and 14 poster papers were carefully reviewed and selected from 53 submissions. They are grouped into the following topics: technology and systems; theoretical and design aspects; health and wellbeing; extended realities; soft and social skills; academic skills; and posters and exhibits.Table of ContentsTechnology and Systems.- Theoretical and Design Aspects.- Health and Wellbeing.- Extended Realities.- Soft and Social Skills.- Academic Skills.- Posters and Exhibits.

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Book SynopsisThis book constitutes the refereed proceedings of the second International Workshop on Cancer Prevention through Early Detection, CaPTion, held in conjunction with the 26th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2023, in Vancouver, Canada, in October 2023.The 11 papers presented at CaPTion 2023 were carefully reviewed and selected from 12 submissions. The workshop invites researchers to submit their work in the field of medical image analysis around the central theme of cancer and early cancer detection, progression, inflammation understanding, multimodality data, and computer-aided navigation.

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Book Synopsis​This book constitutes the refereed proceedings of the 8th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2023, held in conjunction with the 26th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2023, in Vancouver, Canada, in October 2023.The 10 full papers presented at PIPPI 2023 were carefully reviewed and selected from 14 submissions. PIPPI 2023 workshop complements the main MICCAI conference by providing a focused discussion on the challenges of image analysis techniques as applied to the fetal and infant settings.

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Book SynopsisThis book constitutes the refereed proceedings of the 11th Iberoamerican Conference on Applications and Usability of Interactive TV, jAUTI 2022, Cordoba, Spain, November 17–18, 2022. The 9 full papers included in this book were carefully reviewed and selected from 25 submissions. They were organized in topical sections as follows: Content Creation and Interaction, Audiovisual Consumption, e-inclusion, Digital Infrastructure. Table of Contents​Content Creation and Interaction.- Personalized Web-based Contents, generated through a Cross-media Environment, as Additional Information to Documentary Video.- MNEMOSCOPE - A model for digital co-creation and visualization of collective memories.- Dynamic configuration of panoramic virtual tours.- Audiovisual Consumption.- Personalized notifications for the TV ecosystem: field trial of an iTV solution.- Combining Text-To-Speech Services with Conventional Voiceover for News Oralization.- e-inclusion.- iTV to connect generations: a field trial of a solution to send personalized notifications.- Digital Infrastructure.- Encryption of Messages and Additional Information in Digital Terrestrial Television’s Transport Stream Using PSI/SI Tables.- On Using a Microearthquake Recognition System for an Early Warning System at Cotopaxi Volcano.- Using eye tracking to map attention in an EEG-based brainwave graphic visualization system.-Evaluating Perceived Value and Intention to Continue Using Over-the-Top Services in Latin America: A Case Study in Quito, Ecuador.

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Book SynopsisThis book constitutes the refereed proceedings of the ​Second Workshop on Artificial Intelligence over Infrared Images for Medical Applications, AIIIMA 2023 held in conjunction with MICCAI 2023, held in Vancouver, BC, Canada, on October 2, 2023. The 10 full papers presented in this book were carefully peer reviewed and selected from 15 submissions. The second workshop on AIIIMA, similarily to the first, aimes to create a forum to discuss the specific sub-topic of AI over Infrared Images for Medical Applications at MICCAI and promote this novel area of research, that has the potential to hugely impact our society, among the research community.Table of ContentsArtificial Intelligence over Infrared Images for Medical Applications.- The Socioeconomic Impact of Artificial Intelligence Applications in Diagnostic Medical Thermography: A Comparative Analysis with Mammography in Breast Cancer Detection and other diseases early detection.- 3D-BreastNet: A Self-supervised Deep Learning Network for Reconstruction of 3D Breast Surface from 2D Thermal Images.- Modeling the 3D Breast Surface Using Thermography.- 3D Convolutional Neural Networks for Dynamic Breast Infrared Imaging Classification.- Could the consideration of symmetry be statistically significant for breast infrared analysis?.- Performance Evaluation of Convolutional Segmentation Models with Human Hand Thermal Images (H2TI) Dataset.- A Generative Approach for Image Registration of Visible-Thermal (VT) Cancer Faces.- Relationship between thermography assessment and hamstring isometric test in amateur soccer players.- Evaluation of Deep Learning Models for Lower Extremity Muscle Segmentation in Thermal Imaging.- Radiomics feature selection from Thyroid thermal images to improve thyroid nodules interpretations.

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Book SynopsisThis book constitutes the referred proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2022, Virtual Event, February 6–8, 2022. The 15 full papers included in this book were carefully reviewed and selected from 392 submissions. The purpose of VISIGRAPP is to bring together researchers and practitioners interested in both theoretical advances and applications of computer vision, computer graphics and information visualization. VISIGRAPP is composed of four co-located conferences, each specialized in at least one of the aforementioned main knowledge areas, namely GRAPP, IVAPP, HUCAPP and VISAPP. Table of ContentsPapers.- Automatic Threshold RanSaC Algorithms for Pose Estimation Tasks.- Semi-Automated Generation of Accurate Ground-Truth for 3D Object Detection.- A Quantitative and Qualitative Analysis on a GAN-based Face Mask Removal on Masked Images and Videos.- A Quantitative and Qualitative Analysis on a GAN-based Face Mask Removal on Masked Images and Videos.- Partial Alignment of Time Series for Action and Activity Prediction.- Automatic Bi-LSTM Architecture Search Using Bayesian Optimisation for Vehicle Activity Recognition.- ANTENNA: Visual Analytics of Mobility Derived from Cellphone Data.- Influence of Errors on the Evaluation of Text Classification Systems.- Autonomous Navigation Method Considering Passenger Comfort Recognition for Personal Mobility Vehicles in Crowded Pedestrian Spaces.- The Electrodermal Activity of Player Experience in Virtual Reality Games: An Extended Evaluation of the Phasic Component.- MinMax-CAM: Increasing Precision of Explaining Maps by Contrasting Gradient Signals and Regularizing Kernel Usage.- DIAR: Deep Image Alignment and Reconstruction Using Swin Transformers.- Active Learning with Data Augmentation Under Small vs Large Dataset Regimes for Semantic-KITTI Dataset.- Transformers in Unsupervised Structure-from-Motion.- A Study of Aerial Image-based 3D Reconstructions in a Metropolitan Area.

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Book SynopsisThe five-volume set LNCS 14355, 14356, 14357, 14358 and 14359 constitutes the refereed proceedings of the 12th International Conference on Image and Graphics, ICIG 2023, held in Nanjing, China, during September 22–24, 2023.The 166 papers presented in the proceedings set were carefully reviewed and selected from 409 submissions. They were organized in topical sections as follows: computer vision and pattern recognition; computer graphics and visualization; compression, transmission, retrieval; artificial intelligence; biological and medical image processing; color and multispectral processing; computational imaging; multi-view and stereoscopic processing; multimedia security; surveillance and remote sensing, and virtual reality.The ICIG 2023 is a biennial conference that focuses on innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. It will feature world-class plenary speakers, exhibits, and high-quality peer reviewed oral and poster presentations.Table of Contents​Biological and Medical Image Processing: An efficient medical image fusion via online convolutional sparse coding with sample-dependent dictionary.- Multimodal Medical Image Fusion based on Multichannel Aggregated Network.- Multi-Path Feature Fusion and Channel Feature Pyramid for Brain Tumor Segmentation in MRI.- Near infrared video heart rate detection based on multi-region selection and robust principal component analysis- Neural video: A novel framework for interpreting the spatiotemporal activities of the human brain.- Local Fusion Synthetic CT Network for Improving the Quality of CBCT in Cervical Cancer Radiotherapy.- Causality-Inspired Source-Free Domain Adaptation for Medical Image Classification.- Pixel-Correlation-Based Scar Screening in Hypertrophic Myocardium.- Dictionary Matching Based 2D Thin Slice Generalized Slice-dithered Enhanced Resolution (gSlider) Variable Flip Angle T1 Mapping.- Deep Low-rank Multimodal Fusion with Inter-modal Distribution Difference Constraint for ASD Diagnosis.- Cross-domain Tongue Image Segmentation based on Deep Adversarial Networks and Entropy Minimization.- Residual Inter-slice Feature Learning for 3D Organ Segmentation.- Color and Multispectral Processing: A Cross-paired Wavelet Based Spatiotemporal Fusion Network for Remote Sensing Images.- Coupled Dense Convolutional Neural Networks with Autoencoder For Unsupervised Hyperspectral Super Resolution.- Computational Imaging: Multi-scale Non-Local Bidirectional Fusion for Video Super-Resolution.- Multi-View and Stereoscopic Processing: Learning a Deep Fourier Channel Attention Generative Adversarial Network for Light Field Image Super-Resolution.- Synthesizing a large scene with multiple NeRFs.- Neural Implicit 3D Shapes from Single Images with Spatial Patterns.- Multimedia Security: Dense Visible Watermark Removal with Progressive Feature Propagation.- When Diffusion Model Meets with Adversarial Attack: Generating Transferable Adversarial Examples on Face Recognition.- TPM: Two-stage prediction mechanism for universal adversarial patch defense.- Surveillance and remote sensing: WSAD-Net: Weakly Supervised Anomaly Detection in Untrimmed Surveillance Videos.- Multi-object Tracking in Remote Sensing Video Based on Motion and Multi-scale Local Cost Volume.- Density Map Augmentation-based Point-to-point Vehicle Counting and Localization in Remote Sensing Imagery with Limited Resolution.- Large Window Attention based Transformer Network for Change Detection of Remote Sensing Images.- U-TEN:An Unsupervised Two-branch Enhancement Network for Object Detection under Complex-Light Condition.- Virtual Reality: Design of virtual assembly guidance system based on mixed reality.- Blind Omnidirectional Image Quality Assessment Based on Swin Transformer with Scanpath-Oriented.- Audio-visual Saliency for Omnidirectional Videos.

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Book SynopsisThis book consists of full papers presented in the 2nd workshop of ”Medical Image Learning with Noisy and Limited Data (MILLanD)” held in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023).The 24 full papers presented were carefully reviewed and selected from 38 submissions. The conference focused on challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.Table of Contents​Efficient Annotation and Training Strategies.- Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-quality Annotations.- ScribSD: Scribble-supervised Fetal MRI Segmentation based on Simultaneous Feature and Prediction Self-Distillation.- Label-efficient Contrastive Learning-based Model for Nuclei Detection and Classification in 3D Cardiovascular Immunofluorescent Images.- Affordable Graph Neural Network Framework using Topological Graph Contraction.- Approaches for Noisy, Missing, and Low Quality Data.- Dual-domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-angle Reconstruction of Low-dose Cardiac SPECT.- A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain Imaging.- COVID-19 Lesion Segmentation Framework for the Contrast-enhanced CT in the Absence of Contrast-enhanced CT Annotation.- Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Image.- Unsupervised, Self-supervised, and Contrastive Learning.- Decoupled Conditional Contrastive Learning with Variable Metadata for Prostate Lesion Detection.- FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation.- Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation Microscopy.- Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning.- SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction.- Robust Unsupervised Image to Template Registration Without Image Similarity Los.- A Dual-Branch Network with Mixed and Self-Supervision for Medical Image Segmentation: An Application to Segment Edematous Adipose Tissue.- Weakly-supervised, Semi-supervised, and Multitask Learning.- Combining Weakly Supervised Segmentation with Multitask Learning for Improved 3D MRI Brain Tumour Classification.- Exigent Examiner and Mean Teacher: An Advanced 3D CNN-based Semi-Supervised Brain Tumor Segmentation Framework.- Extremely Weakly-supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation.- Multi-Task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Image.- Active Learning.- Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach.- Test-time Augmentation-based Active Learning and Self-training for Label-efficient Segmentation.- Active Transfer Learning for 3D Hippocampus Segmentation.- Transfer Learning.- Using Training Samples as Transitive Information Bridges in Predicted 4D MRI.- To Pretrain or not to Pretrain? A Case Study of Domain-Specific Pretraining for Semantic Segmentation in Histopathology.- Large-scale Pretraining on Pathological Images for Fine-tuning of Small Pathological Benchmarks.

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Book SynopsisThis volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA.The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as:Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture.Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster.Table of ContentsVirtual Reality.- A Pilot Study Comparing User Interactions Between Augmented and Virtual Reality.- Synthesizing Play-Ready VR Scenes with Natural Language Prompts through GPT API.- Emergent Individual Factors for AR Education and Training.- Segmentation.- ISLE: A Framework for Image Level Semantic Segmentation Ensemble.- Particulate Mapping Centerline Extraction (PMCE), a Novel Centerline Extraction Algorithm Based on Patterns in the Spatial Distribution of Aggregates.- Evaluating Segmentation Approaches on Digitized Herbarium Specimens.- Semantic Scene Filtering for Event Cameras in Long-Term Outdoor Monitoring Scenarios.- SODAWideNet - Salient Object Detection with an Attention augmented Wide Encoder Decoder network without ImageNet pre-training.- Applications.- Foil-Net: Deep Learning-Based Wave Classification for Hydrofoil Surfing.- Inpainting of Depth Images using Deep Neural Networks for Real-Time Applications.- Using 2D and 3D Face Representations to Generate Comprehensive Facial Electromyography Intensity Maps.- Real-world Image Deblurring via Unsupervised Domain Adaptation.- Object Detection and Recognition.- Reliable Matching by Combining Optimal Color and Intensity Information based on Relationships between Target and Surrounding Objects.- Regularized Meta-Training with Embedding Mixup for Improved Few-Shot Learning.- Visual Foreign Object Detection for Wireless Charging of Electric Vehicles.- Deep Representation Learning for License Plate Recognition in Low Quality Video Images.- Optimizing PnP-Algorithms for Limited Point Correspondences Using Spatial Constraints.- Deep Learning.- Unsupervised Deep-Learning Approach for Underwater Image Enhancement.- LaneNet++ : Uncertainty-aware Lane Detection for Autonomous Vehicle.- Task-driven Compression for Collision Encoding based on Depth Images.- Eigenpatches - Adversarial Patches from Principal Components.- Edge-guided Image Inpainting with Transformer.- Poster.- Bayesian Fusion inspired 3D reconstruction via LiDAR-Stereo Camera Pair.- Marimba Mallet Placement Tracker.- DINO-CXR: A Self Supervised Method Based on Vision Transformer for Chest X-Ray Classification.- Social Bias and Image Tagging: Evaluation of Progress in State-of-the-Art Models.- L-TReiD: Logic Tensor Transformer for Re-Identification.- Retinal Disease Diagnosis with a Hybrid ResNet50-LSTM Deep Learning Model.- Pothole Segmentation and Area Estimation with Deep Neural Networks and Unmanned Aerial Vehicles.- Generation method of robot assembly motion considering physicality gap between humans and robots.- A Self-Supervised Pose Estimation Approach for Construction Machines.- Image Quality Improvement of Surveillance Camera Images by Learning Noise Removal Method Using Noise2Noise.- Automating Kernel Size Selection in MRI Reconstruction via a Transparent and Interpretable Search Approach.- Segmentation and Identification of Mediterranean Plant Species.- Exploiting Generative Adversarial Networks in Joint Sensitivity Encoding for Enhanced MRI Reconstruction.- Multisensory Modeling of Tabular Data for Enhanced Perception and Immersive User Experience.- Coping with Bullying Incidents by the Narrative and Multi-modal Interaction in Virtual Reality.

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Book SynopsisThis volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA.The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as:Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture.Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster.Table of ContentsST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management.- Hybrid Region and Pixel-Level Adaptive Loss for Mass Segmentation on Whole Mammography Images.- Deep Learning Based GABA Edited-MRS Signal Reconstruction.- Investigating the Impact of Attention on Mammogram Classification.- ReFit:A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images.- A Data-centric Approach for Pectoral Muscle Deep Learning Segmentation Enhancements in Mammography Images.- Visualization.- Visualizing Multimodal Time Series at Scale.- Hybrid Tree Visualizations for Analysis of Gerrymandering.- ArcheryVis: A Tool for Analyzing and Visualizing Archery Performance Data.- Spiro: Order-preserving Visualization in High Performance Computing Monitoring.- From Faces To Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans.- Video Analysis and Event Recognition.- Comparison of Autoencoder Models for Unsupervised Representation Learning of Skeleton Sequences.- Local and Global Context Reasoning for Spatio-Temporal Action Localization.- Zero-Shot Video Moment Retrieval using BLIP-based Models.- Self-Supervised Representation Learning for Fine Grained Human Hand Action Recognition in Industrial Assembly Lines.- ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures.- Pretext Tasks in Bridge Defect Segmentation within a ViT-Adapter Framework.- A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation.- Efficient Resource Provisioning in Critical Infrastructures based on Multi-Agent Rollout enabled by Deep Q-Learning.- Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer.- ST: Generalization in Visual Machine Learning.- Latent Space Navigation for Face Privacy: A Case Study on the MNIST Dataset.- Domain Generalization for Foreground Segmentation Using Federated Learning.- Probabilistic Local Equivalence Certification for Robustness Evaluation.- Challenges of Depth Estimation for Transparent Objects.- Volumetric Body Composition through Cross-Domain Consistency Training for Unsupervised Domain Adaptation.- Computer Graphics.- Water Animation Using Coupled SPH and Wave Equation.- Neural Rendering into Unity.- Virtual Home Staging: Inverse Rendering and Editing an Indoor Panorama under Natural Illumination.- SwarmCurves: Evolutionary Curve Reconstruction.- Medical Image Analysis.- Brain Cortical Surface Registration with Anatomical Atlas Constraints.- When System Model meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging.- 3D Reconstruction from 2D Cerebral Angiograms as a Volumetric Denoising Problem.- An Integrated Shape-Texture Descriptor for Modeling Whole-Organism Phenotypes in Drug Screening.- Enhancing Image Reconstruction via Phase-Constrained Data in an Iterative Process.- Biometrics.- I Got Your Emotion: Emotion Preserving Face De-identification Using Injection-based Generative Adversarial Networks.- DoppelVer: A Benchmark for Face Verification.- Two-stage Face Detection and Anti-spoofing.- Autonomous Anomaly Detection in Images.- Driver Anomaly Detection Using Skeleton Images.- Driver Anomaly Detection Using Skeleton Images.- Latent Diffusion based Multi-class Anomaly Detection.- ST: Artificial Intelligence in Aerial and Orbital Imagery.- Investigating the impact of a low-rank tensor-based approach on deforestation imagery.- Strategic Incorporation of Synthetic Data for Performance Enhancement in Deep Learning A Case Study on Object Tracking Tasks.- Autonomous Navigation Via A Cascading CNN Framework Leveraging Synthetic Terrain Images.- ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture.- Synthetically labeled images for maize plant detection in UAS images.- An open source simulation toolbox for annotation of images and point clouds in agricultural scenarios.- Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms.- Identification of Abnormality in Maize Plants From UAV Images Using Deep Learning Approaches.- Deep Learning for Super Resolution of Sugarcane Crop Line Imagery from Unmanned Aerial Vehicles.

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Book SynopsisThe two-volume proceedings set LNAI 14338 and 14339 constitutes the refereed proceedings of the 25th International Conference on Speech and Computer, SPECOM 2023, held in Dharwad, India, during November 29–December 2, 2023.The 94 papers included in these proceedings were carefully reviewed and selected from 174 submissions. They focus on all aspects of speech science and technology: ​automatic speech recognition; computational paralinguistics; digital signal processing; speech prosody; natural language processing; child speech processing; speech processing for medicine; industrial speech and language technology; speech technology for under-resourced languages; speech analysis and synthesis; speaker and language identification, verification and diarization.Table of Contents​Industrial Speech and Language Technology.- Analysing Breathing Patterns in Reading and Spontaneous Speech.- Audio-Visual Speaker Verification via Joint Cross Attention.- A Novel Scheme to Classify Read and Spontaneous Speech.- Analysis of a Hinglish ASR System’s Performance for Fraud Detection.- Anomaly Detection in Speech: A Comprehensive Approach for Enhanced Speech Analysis.- CAPTuring Accents: An Approach to Personalize Pronunciation Training for Learners with Different L1 Backgrounds.- Speech Technology for Under-Resourced Languages.- Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Languages.- Phone Durations Modeling for Livvi-Karelian ASR.- Significance of Indic Self-Supervised Speech Representations for Indic Under-Resourced ASR.- Study of Various End-to-End Keyword Spotting Systems on the Bengali language under Low-Resource Condition.- Bridging the Gap: Towards Linguistic Resource Development for the Low-Resource Lambani Language.- Studying the Effect of Frame-Level Concatenation of GFCC and TS-MFCC Features on Zero-Shot Children’s ASR.- Code-Mixed Text-to-Speech Synthesis under Low-Resource Constraints.- An End-to-End TTS Model in Chhattisgarhi, a Low-Resource Indian Language.- An ASR Corpus in Chhattisgarhi, a Low Resource Indian Language.- Cross Lingual Style Transfer using Multiscale Loss Function for Soliga: A Low Resource Tribal Language.- Preliminary Analysis of Lambani Vowels and Vowel Classification using Acoustic Feature.- Curriculum Learning based Approach for Faster Convergence of TTS Model.- Rhythm Measures and Language Endangerment: the Case of Deori.- Konkani Phonetic Transcription System 1.0.- Speech Analysis and Synthesis.- E-TTS: Expressive Text-to-Speech Synthesis for Hindi using Data Augmentation.- Direct vs Cascaded Speech-to-Speech Translation using Transformer.- Deep Learning based Speech Quality Assessment Focusing on Noise Effects.- Quantifying the Emotional Landscape of Music with Three Dimensions.- Analysis of Mandarin vs. English Language for Emotional Voice Conversion.- Audio DeepFake Detection Employing Multiple Parametric Exponential Linear Units.- A Comparison of Learned Representations with Jointly Optimized VAE and DNN for Syllable Stress Detection.- On the Asymptotic Behaviour of the Speech Signal.- Improvement of Audio-Visual Keyword Spotting System Accuracy using Excitation Source Feature.- Developing a Question Answering System on the material of Holocaust survivors’ testimonies in Russian.- Enhancing Children’s Short Utterance based ASV using Data Augmentation Techniques and Feature Concatenation Approach.- Studying the Effectiveness of Data Augmentation and Frequency-Domain Linear Prediction Coefficients in Children’s Speaker Verification under Low-Resource Conditions.- Constant-Q based Harmonic and Pitch Features for Normal vs Pathological Infant Cry Classification.- Robustness of Whisper Features for Infant Cry Classification.- Speaker and Language Identification, Verification, and Diarization.- I-MSV 2022: Indic-Multilingual and Multi-Sensor Speaker Verification Challenge.- Multi-Task Learning over Mixup Variants for the Speaker Verification Task.- Exploring the Impact of Different Approaches for Spoken Dialect Identification of Konkani Language.- Adversarially Trained Hierarchical Attention Network for Domain-Invariant Spoken Language Identification.- Ensemble of Incremental System Enhancements for Robust Speaker Diarization in Code-Switched Real-Life Audios.- Enhancing Language Identification in Indian Context through Exploiting Learned Features with Wav2Vec2.0.- Design and Development of Voice OTP Authentication System.- End-to-End Native Language Identification using a Modified Vision Transformer(ViT) from L2 English Speech.- Dialect Identification in Ao using Modulation-based Representation.- Self-Supervised Speaker Verification Employing Augmentation Mix and Self-Augmented Training-based Clustering.

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Book SynopsisThis book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29 – February 2, 2024.The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.Table of ContentsWhere are Biases? Adversarial Debiasing with Spurious Feature Visualization.- Cross-Modal Hash Retrieval with Category Semantics.- Spatiotemporal Representation Enhanced ViT for Video Recognition.- SCFormer: A Vision Transformer with Split Channel in Sitting Posture Recognition.- Dive into Coarse-to-Fine Strategy in Single Image Deblurring.- TICondition: Expanding Control Capabilities for Text-to-Image Generation with Multi-Modal Conditions.- Enhancing Generative Generalized Zero Shot Learning via Multi-Space Constraints and Adapative Integration.- Joint Image Data Hiding and Rate-Distortion Optimization in Neural Compressed Latent Representations.- GSUNet: A Brain Tumor Segmentation Method Based On 3D Ghost Shuffle U-Net.- ACT: Action-associated and Target-related Representations for Object Navigation.- Foreground Feature Enhancement and Peak & Background Suppression for Fine-Grained Visual Classification.- YOLOv5-SRR: Enhancing YOLOv5 for Effective Underwater Target Detection.- Image Clustering and Generation with HDGMVAE-I.- “Car or Bus?" CLearSeg: CLIP-enhanced Discrimination among Resembling Classes for Few-Shot Semantic Segmentation.- PANDA: Prompt-based Context- and Indoor-aware Pretraining for Vision and Language Navigation.- Cross-Modal Semantic Alignment Learning for Text-based Person Search.- Point Cloud Classification via Learnable Memory Bank.- Adversarially Regularized Low-Light Image Enhancement.- Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation.- PMGCN:Preserving measuring mapping prototype graph calibration network for few-shot learning.- ARE-CAM: An interpretable approach to quantitatively evaluating the adversarial robustness of deep models based on CAM.- SSK-Yolo:Global feature-driven small object detection network for images.- MetaVSR: A Novel Approach to Video Super-Resolution for Arbitrary Magnification.- From Skulls to Faces: A Deep Generative Framework for Realistic 3D Craniofacial Reconstruction.- Structure-aware Adaptive Hybrid Interaction Modeling for Image-Text Matching.- Using Saliency and Cropping to Improve Video Memorability.- Contextual Augmentation with Bias Adaptive for Few-shot VideoObject Segmentation.- A lightweight local attention network for image super resolution.- Domain Adaptation for Speaker Verification Based on Self-SupervisedLearning with Adversarial Training.- Quality Scalable Video Coding based on Neural Representation.- Hierarchical Bi-Directional Temporal Context Mining for ImprovedVideo Compression.- MAMixer: Multivariate Time Series Forecasting via Multi-Axis Mixing.- A Custom GAN-based Robust Algorithm for Medical Image Watermarking.- A Detail-guided Multi-source Fusion Network for Remote Sensing Object Detection.- A Secure and Fair Federated Learning Protocol under the Universal Composability Framework.- Bi-directional Interaction and Dense Aggregation Network for RGB-D Salient Object Detection.- Face Forgery Detection via Texture and Saliency Enhancement.

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Book SynopsisBONBID-HIE 2023.- Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation.- Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy.- An Ensemble Approach for Segmentation of Neonatal HIE lesions.- Improving Segmentation of Hypoxic Ischemic Encephalopathy Lesions by Heavy Data Augmentation: Contribution to the BONBID Challenge.- A Deep Neural Network Approach for the Lesion Segmentation from Neonatal Brain Magnetic Resonance Imaging.- SegResNet based Reciprocal Transformation for BONBID-HIE Lesion Segmentation.- Trauma THOMPSON 2023.- Overview of the Trauma THOMPSON Challenge at MICCAI 2023.- The Trauma THOMPSON Challenge Report MICCAI 2023.- Action Recognition and Action Anticipation Tasks in the Trauma THOMPSON Challenge Technical Report.- QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View.

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Book SynopsisCOHO: Context-Sensitive City-Scale Hierarchical Urban Layout Generation.- Joint RGB-Spectral Decomposition Model Guided Image Enhancement in Mobile Photography.- SpatialFormer: Towards Generalizable Vision Transformers with Explicit Spatial Understanding.- OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving.- MyVLM: Personalizing VLMs for User-Specific Queries.- AMEGO: Active Memory from long EGOcentric videos.- Power Variable Projection for Initialization-Free Large-Scale Bundle Adjustment.- Collaborative Control for Geometry-Conditioned PBR Image Generation.- Co-synthesis of Histopathology Nuclei Image-Label Pairs using a Context-Conditioned Joint Diffusion Model.- One-stage Prompt-based Continual Learning.- SpaceJAM: a Lightweight and Regularization-free Method for Fast Joint Alignment of Images.- APL: Anchor-based Prompt Learning for One-stage Weakly Supervised Referring Expression Comprehension.- GenQ: Quantization in Low Data Regimes with Generative Synthetic Data.- MVDD: Multi-View Depth Diffusion Models.- Rethinking Video-Text Understanding: Retrieval from Counterfactually Augmented Data.- Risk-Aware Self-Consistent Imitation Learning for Trajectory Planning in Autonomous Driving.- Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud Segmentation.- EBDM: Exemplar-guided Image Translation with Brownian-bridge Diffusion Models.- DreamDrone: Text-to-Image Diffusion Models are Zero-shot Perpetual View Generators.- Harnessing Text-to-Image Diffusion Models for Category-Agnostic Pose Estimation.- SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer.- Overcoming Distribution Mismatch in Quantizing Image Super-Resolution Networks.- Large Motion Model for Unified Multi-Modal Motion Generation.- FisherRF: Active View Selection and Mapping with Radiance Fields using Fisher Information.- Occlusion Handling in 3D Human Pose Estimation with Perturbed Positional Encoding.- Gradient-based Out-of-Distribution Detection.- Event-based Mosaicing Bundle Adjustment.

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Book SynopsisSimPB: A Single Model for 2D and 3D Object Detection from Multiple Cameras.- EMDM: Efficient Motion Diffusion Model for Fast, High-Quality Human Motion Generation.- Editable Image Elements for Controllable Synthesis.- Improving 2D Feature Representations by 3D-Aware Fine-Tuning.- Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection.- PCF-Lift: Panoptic Lifting by Probabilistic Contrastive Fusion.- SemGrasp: Semantic Grasp Generation via Language Aligned Discretization.- MANIKIN: Biomechanically Accurate Neural Inverse Kinematics for Human Motion Estimation.- Simple Unsupervised Knowledge Distillation With Space Similarity.- DragAPart: Learning a Part-Level Motion Prior for Articulated Objects.- Diffusion Bridges for 3D Point Cloud Denoising.- Optimizing Illuminant Estimation in Dual-Exposure HDR Imaging.- BAM-DETR: Boundary-Aligned Moment Detection Transformer for Temporal Sentence Grounding in Videos.- MarineInst: A Foundation Model for Marine Image Analysis with Instance Visual Description.- Superpixel-informed Implicit Neural Representation for Multi-Dimensional Data.- EgoPoser: Robust Real-Time Egocentric Pose Estimation from Sparse and Intermittent Observations Everywhere.- Physics-Free Spectrally Multiplexed Photometric Stereo under Unknown Spectral Composition.- SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction.- VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models.- Alignist: CAD-Informed Orientation Distribution Estimation by Fusing Shape and Correspondences.- Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs.- Physics-Based Interaction with 3D Objects via Video Generation.- Reconstruction and Simulation of Elastic Objects with Spring-Mass 3D Gaussians.- Deep Patch Visual SLAM.- Surface Reconstruction for 3D Gaussian Splatting via Local Structural Hints.- HeadGaS: Real-Time Animatable Head Avatars via 3D Gaussian Splatting.- LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow.

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