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• A Study of Energy Reduction Strategies in Renewable Hybrid Grid.- Classification and Watermarking of Brain Tumor using Artificial and Convolutional Neural Networks.- A Proposal for a Deep Learning Model to Enhance Student Guidance and Reduce Dropout.- EduBot: An Unsupervised Domain-Specific Chatbot for Educational Institutions.- SQL Generation from Natural Language using Supervised Learning and Recurrent Neural Networks.- Toward Intelligent Solution to Identify Learner Attitude from Source Code.
• (source: Nielsen Book Data)

This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
• (source: Nielsen Book Data)

The five-volume set LNCS 10111-10115 constitutes the thoroughly refereed post-conference proceedings of the 13th Asian Conference on Computer Vision, ACCV 2016, held in Taipei, Taiwan, in November 2016. The total of 143 contributions presented in these volumes was carefully reviewed and selected from 479 submissions. The papers are organized in topical sections on Segmentation and Classification; Segmentation and Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions; Faces; Computational Photography; Face and Gestures; Image Alignment; Computational Photography and Image Processing; Language and Video; 3D Computer Vision; Image Attributes, Language, and Recognition; Video Understanding; and 3D Vision.
(source: Nielsen Book Data)

• New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
• (source: Nielsen Book Data)

The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected .
(source: Nielsen Book Data)

• New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
• (source: Nielsen Book Data)

The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected .
(source: Nielsen Book Data)

• New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
• (source: Nielsen Book Data)

The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected .
(source: Nielsen Book Data)

• 1. The vision of sociable robots
• 2. Robot in society: a question of interface
• 3. Insights from developmental psychology
• 4. Designing sociable robots
• 5. The physical robot
• 6. The vision system
• 7. The auditory system
• 8. The motivation system
• 9. The behavior system
• 10. Facial animation and expression
• 11. Expressive vocalization system
• 12. Social constraints on animate vision
• 13. Grand challenges of building sociable robots.

Cynthia Breazeal here presents her vision of the sociable robot of the future, a synthetic creature and not merely a sophisticated tool. A sociable robot will be able to understand us, to communicate and interact with us, to learn from us and grow with us. It will be socially intelligent in a humanlike way. Eventually sociable robots will assist us in our daily lives, as collaborators and companions. Because the most successful sociable robots will share our social characteristics, the effort to make sociable robots is also a means for exploring human social intelligence and even what it means to be human. Breazeal defines the key components of social intelligence for these machines and offers a framework and set of design issues for their realization. Much of the book focuses on a nascent sociable robot she designed named Kismet. Breazeal offers a concrete implementation for Kismet, incorporating insights from the scientific study of animals and people, as well as from artistic disciplines such as classical animation. This blending of science, engineering, and art creates a lifelike quality that encourages people to treat Kismet as a social creature rather than just a machine. The book includes a CD-ROM that shows Kismet in action.
(source: Nielsen Book Data)

Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn * Learn the introductory concepts of machine learning. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
(source: Nielsen Book Data)

Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn * Learn the introductory concepts of machine learning. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
(source: Nielsen Book Data)

• Combinatorial tools
• Discretization
• Discrete tomography
• Discrete and combinatorial topology.-Shape descriptors
• Models for discrete geometry
• Circle drawing
• Morphological analysis
• Geometric transforms
• Discrete shape representation, recognition and analysis.

This book constitutes the refereed proceedings of the 19th IAPR International Conference on Discrete Geometry for Computer Imagery, DGCI 2016, held in Nantes, France, in April 2016. The 32 revised full papers presented together with 2 invited talks were carefully selected from 51 submissions. The papers are organized in topical sections on combinatorial tools; discretization; discrete tomography; discrete and combinatorial topology; shape descriptors; models for discrete geometry; circle drawing; morphological analysis; geometric transforms; and discrete shape representation, recognition and analysis.

• Clustering and Quantum Methods.- Motion and Tracking.- Image Processing and Segmentation.- Color, Shading and Reflectance of Light.- Propagation and Time-evolution.- Inference, Labeling, and Relaxation.
• (source: Nielsen Book Data)

This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation.
(source: Nielsen Book Data)

• Character and text recognition.- Document image processing.- Segmentation and layout analysis.- Word embedding and spotting.- Text detection.- Font design and classification.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 14th IAPR International Workshop on Document Analysis Systems, DAS 2020, held in Wuhan, China, in July 2020. The 40 full papers presented in this book were carefully reviewed and selected from 57 submissions. The papers are grouped in the following topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text detection; and font design and classification. Due to the Corona pandemic the conference was held as a virtual event .
(source: Nielsen Book Data)

• Pattern Recognition and Machine Learning
• Spatiotemporal Stacked Sequential Learning for Pedestrian Detection
• Social Signaling Descriptor for Group Behaviour Analysis
• A New Smoothing Method for Lexicon-Based Handwritten Text Keyword Spotting
• Empirical Evaluation of Different Feature Representations for Social Circles Detection
• Source-Target-Source Classification Using Stacked Denoising Autoencoders
• On the Impact of Distance Metrics in Instance-Based Learning Algorithms
• Multi-class Boosting for Imbalanced Data
• Computer Vision
• Object Discovery Using CNN Features in Egocentric Videos
• Prototype Generation on Structural Data Using Dissimilarity Space Representation: A Case of Study
• Estimation and Tracking of Partial Planar Templates to Improve VSLAM
• Human Centered Scene Understanding Based on 3D Long-Term Tracking Data
• Fast Head Pose Estimation for Human-Computer Interaction
• Structured Light System Calibration for Perception in Underwater Tanks
• Dense 3D SLAM in Dynamic Scenes Using Kinect
• Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics
• System for Medical Mask Detection in the Operating Room Through Facial Attributes
• Image and Signal Processing
• New Method for Obtaining Optimal Polygonal Approximations
• Noise Decomposition Using Polynomial Approximation
• Color Correction for Image Stitching by Monotone Cubic Spline Interpolation
• Structured Output Prediction with Hierarchical Loss Functions for Seafloor Imagery Taxonomic Categorization
• Escaping Path Approach with Extended Neighborhood for Speckle Noise Reduction
• Adaptive Line Matching for Low-Textured Images
• Unsupervised Approximation of Digital Planar Curves
• On the Modification of Binarization Algorithms to Retain Grayscale Information for Handwritten Text Recognition
• Applications
• Improving the Minimum Description Length Inference of Phrase-Based Translation Models
• A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients
• Arabic Writer Identification Using Local Binary Patterns (LBP) of Handwritten Fragments
• A Fuzzy C-Means Algorithm for Fingerprint Segmentation
• Word-Graph Based Applications for Handwriting Documents: Impact of Word-Graph Size on Their Performances
• Temporal Segmentation of Digital Colposcopies
• Goal-Driven Phenotyping Through Spectral Imaging for Grape Aromatic Ripeness Assessment
• Medical Image
• Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI
• Kernel-Based Feature Relevance Analysis for ECG Beat Classification
• Spatial-Dependent Similarity Metric Supporting Multi-atlas MRI Segmentation
• Color Detection in Dermoscopy Images Based on Scarce Annotations
• Pattern Recognition and Machine Learning
• Spectral Clustering Using Friendship Path Similarity
• R-Clustering for Egocentric Video Segmentation
• Applying Basic Features from Sentiment Analysis for Automatic Irony Detection
• Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data
• Time-Series Prediction Based on Kernel Adaptive Filtering with Cyclostationary Codebooks
• Latent Topic Encoding for Content-Based Retrieval
• Dissimilarity-Based Learning from Imbalanced Data with Small Disjuncts and Noise
• Binary and Multi-class Parkinsonian Disorders Classification Using Support Vector Machines
• Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models
• Measuring Scene Detection Performance
• Threshold of Graph-Based Volumetric Segmentation
• Brain Neural Data Analysis with Feature Space Defined by Descriptive Statistics
• Extremely Overlapping Vehicle Counting
• Sentence Clustering Using Continuous Vector Space Representation
• Online Learning of Stochastic Bi-automaton to Model Dialogues
• Single-Channel Separation Between Stationary and Non-stationary Signals Using Relevant Information
• Computer Vision
• A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15)
• Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents
• Person Enrollment by Face-Gait Fusion
• Homographic Class Template for Logo Localization and Recognition
• Multimodal Object Recognition Using Random Clustering Trees
• Videogrammetry System for Wind Turbine Vibration Monitoring
• Canonical Views for Scene Recognition in Mobile Robotics
• Crater Detection in Multi-ring Basins of Mercury
• Iterative Versus Voting Method to Reach Consensus Given Multiple Correspondences of Two Sets
• Extracting Categories by Hierarchical Clustering Using Global Relational Features
• A Calibration Algorithm for Multi-camera Visual Surveillance Systems Based on Single-View Metrology
• 3D-Guided Multiscale Sliding Window for Pedestrian Detection
• A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios
• Image and Signal Processing
• Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination
• Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition
• PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones
• Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes
• Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity
• Dimension Reduction of Hyperspectral Image with Rare Event Preserving
• Applications
• Clustering of Strokes from Pen-Based Music Notation: An Experimental Study
• Image Analysis-Based Automatic Detection of Transmission Towers Using Aerial Imagery
• A Sliding Window Framework for Word Spotting Based on Word Attributes
• Combining Statistical and Semantic Knowledge for Sarcasm Detection in Online Dialogues
• Estimating Fuel Consumption from GPS Data
• A Bag-of-phonemes Model for Homeplace Classification of Mandarin Speakers
• A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation
• Genetic Seam Carving: A Genetic Algorithm Approach for Content-Aware Image Retargeting
• Analysis of Expressiveness of Portuguese Sign Language Speakers
• Automatic Eye Localization; Multi-block LBP vs. Pyramidal LBP Three-Levels Image Decomposition for Eye Visual Appearance Description
• Clinical Evaluation of an Automatic Method for Segmentation and Characterization of the Thoracic Aorta with and Without Aneurysm Patients
• Combined MPEG7 Color Descriptors for Image Classification: Bypassing the Training Phase
• A Multi-platform Graphical Software for Determining Reproductive Parameters in Fishes Using Histological Image Analysis.

This book constitutes the proceedings of the 7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015, held in Santiage de Compostela, Spain, in June 2015. The 83 papers presented in this volume were carefully reviewed and selected from 141 submissions. They were organized in topical sections named: Pattern Recognition and Machine Learning; Computer Vision; Image and Signal Processing; Applications; Medical Image; Pattern Recognition and Machine Learning; Computer Vision; Image and Signal Processing; and Applications.

• Pattern Recognition and Machine Learning.- Computer Vision.- Image and Signal Processing.- Medical Image.-Applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 8th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2017, held in Faro, Portugal, in June 2017. The 60 regular papers presented in this volume were carefully reviewed and selected from 86 submissions. They are organized in topical sections named: Pattern Recognition and Machine Learning; Computer Vision; Image and Signal Processing; Medical Image; and Applications.
(source: Nielsen Book Data)

• Facial Age Estimation Using Compact Facial Features.- A Vision Based Hardware-Software Real-Time Control System for the Autonomous Landing of an UAV.- Exploration of Ear Biometrics with Deep Learning.- Does Randomness in the Random Visual Cryptography Protocol Depend on the Period of Pseudorandom Number Generators.- Software for CT-Image Analysis to Assist the Choice of Mechanical-Ventilation Settings in Acute Respiratory Distress Syndrome.- Edge-Aware Color Image Manipulation by Combination of Low-pass Linear Filter and Morphological Processing of its Residuals.- On the Effect of DCE MRI Slice Thickness and Noise on Estimated Pharmacokinetic Biomarkers a Simulation Study.- A New Sport Teams Logo Dataset for Detection Tasks.- Scene Recognition Using AlexNet to Recognize Significant Events within Cricket Game Footage.- Biologically Inspired Modelling of Flowers.- Tuberculosis Abnormality Detection in Chest X-Rays: A Deep Learning Approach.- Dynamic Local Ternary Patterns for Gender Identification using Facial Components.- Depth Perception Tendencies in the 3-D Environment of Virtual Reality.- Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking.- Nuclei Detection with Local Threshold Processing in DAB&H Stained Breast Cancer Biopsy Images.- Video Footage Highlight Detection in Formula 1 Through Vehicle Recognition with Faster R-CNN Trained On Game Footage.- Performance Evaluation of Selected Detector-Descriptor Combinations.- Watermarking Method for Video Authentication with Tamper Localization.- RGB-D and Lidar Calibration Supported by GPU.- Video-Surveillance Tools for Monitoring Social Responsibility Under Covid-19 Restrictions.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2020, held in Warsaw, Poland, in September 2020. The 20 full papers were selected from 49 submissions. The contributions cover topics such as: modelling of human visual perception; computational geometry; geometrical models of objects and scenes; illumination and reflection models and methods; image formation; image and video coding; image filtering and enhancement; biomedical image processing; biomedical graphics; colour image processing; multispectral image processing; pattern recognition in image processing; scene understanding; motion analysis, visual navigation and active vision; human motion detection and analysis; visualisation and graphical data presentation; hardware and architectures for image processing; computer-aided graphic design; 3D imaging, shading and rendering; computer animation; graphics for internet and mobile systems; virtual reality; image and video databases; digital watermarking; multimedia applications; and computer art. Due to the Corona pandemic ICCVG 2020 was held as a virtual event.
(source: Nielsen Book Data)

• Modelling of Subjective Radiological Assessments with Objective Image Quality Measures of Brain and Body CT Images
• Blind Image Quality Assessment Through Wakeby Statistics Model
• Improving Image Quality of Tiled Displays
• Structural Similarity-Based Optimization Problems with L1-Regularization: Smoothing Using Mollifiers
• Improved Non-Local Means Algorithm Based on Dimensionality Reduction
• Non-local Means for Stereo Image Denoising Using Structural Similarity
• Structural Similarity Optimized Wiener Filter: A Way to Fight Image Noise
• A Real-Time Framework for Detection of Long Linear Infrastructural Objects in Aerial Imagery
• Structural Representations for Multi-modal Image Registration Based on Modified Entropy
• Attributed Relational Graph-Based Learning of Object Models for Object Segmentation
• Label Fusion for Multi-atlas Segmentation Based on Majority Voting
• An Optimized Selective Encryption for Video Confidentiality
• Near-Lossless PCA-Based Compression of Seabed Surface with Prediction
• Adaptive Weighted Neighbors Lossless Image Coding
• Dimensionality Reduction of Proportional Data Through Data Separation Using Dirichlet Distribution
• Image Categorization Using a Heuristic Automatic Clustering Method Based on Hierarchical Clustering
• Semantic Scene Classification with Generalized Gaussian Mixture Models
• Classification of Tooth Shapes for Human Identification Purposes
• An Experimental Comparison of Selected Simple Shape Descriptors
• Micro Genetic and Evolutionary Feature Extraction: An Exploratory Data Analysis Approach for Multispectral Iris Recognition
• Biometric Analysis of Human Ear Matching Using Scale and Rotation Invariant Feature Detectors
• Mutibiometric System Based on Game Theory
• Head Pose Classification Using a Bidimensional Correlation Filter
• Illumination Robust Facial Feature Detection via Decoupled Illumination and Texture Features
• Posed Facial Expression Detection Using Reflection Symmetry and Structural Similarity
• Improving the Recognition of Occluded Faces by Means of Two-Dimensional Orthogonal Projection into Local Subspaces
• Hybrid Age Estimation Using Facial Images
• Unsupervised Sub-graph Selection and Its Application in Face Recognition Techniques
• Dynamic Perceptual Attribute-Based Hidden Conditional Random Fields for Gesture Recognition
• The Bag of Micro-Movements for Human Activity Recognition
• An Efficient Method for Extracting Key-Frames from 3D Human Joint Locations for Action Recognition
• A Simple View-Based Software Architecture for an Autonomous Robot Navigation System
• A Comparison of Feature Detectors and Descriptors in RGB-D SLAM Methods
• Accuracy Improvement for Depth from Small Irregular Camera Motions and Its Performance Evaluation. Fast and Robust Algorithm for Fundamental Matrix Estimation
• Biologically-Inspired Supervised Vasculature Segmentation in SLO Retinal Fundus Images
• Assessment of Retinal Vascular Changes Through Arteriolar-to-Venular Ratio Calculation
• Automatic Segmentation of Vertebrae in Ultrasound Images
• Towards an Automatic Clinical Classification of Age-Related Macular Degeneration
• Optical Flow Based Approach for Automatic Cardiac Cycle Estimation in Ultrasound Images of the Carotid
• Statistical Textural Distinctiveness in Multi-Parametric Prostate MRI for Suspicious Region Detection
• Automatic Detection of Immunogold Particles from Electron Microscopy Images
• Specular Reflectance Suppression in Endoscopic Imagery via Stochastic Bayesian Estimation
• Characterization of Medical Images Using Edge Density and Local Directional Pattern (LDP)
• Angiography Images for Transcatheter Aortic Valve Implantation Patients
• Retinal Blood Vessels Differentiation for Calculation of Arterio-Venous Ratio
• Graph Structuring of Skeleton Object for Its High-Level Exploitation
• Vehicle Detection Using Approximation of Feature Pyramids in the DFT Domain
• Real-Time Speed-Limit Sign Detection and Recognition Using Spatial Pyramid Feature and Boosted Random Forest
• Automatic Nacre Thickness Measurement of Tahitian Pearls
• Automated Wheat Disease Classification Under Controlled and Uncontrolled Image Acquisition
• Color Space Identification for Image Display
• Application of the General Shape Analysis in Determining the Class of Binary Object Silhouettes in the Video Surveillance System
• Speedy Character Line Detection Algorithm Using Image Block-Based Histogram Analysis
• Detecting Parked Vehicles in Static Images Using Simple Spectral Features in the 'SM4Public' System
• Road Detection in Urban Areas Using Random Forest Tree-Based Ensemble Classification
• Application of the Polar-Fourier Greyscale Descriptor to the Automatic Traffic Sign Recognition
• Camera-Based Lane Marking Detection for ADAS and Autonomous Driving
• Handling Inter-object Occlusion for Multi-object Tracking Based on Attraction Force Constraint
• Indian Sign Language Recognition Using Kinect Sensor
• Automatic Planning of Minimally Invasive Aortic Valve Replacement Surgery.

This book constitutes the thoroughly refereed proceedings of the 12th International Conference on Image Analysis and Recognition, ICIAR 2015, held in Niagara Falls, ON, Canada, in July 2015. The 55 revised full papers and 5 short papers presented were carefully reviewed and selected from 80 submissions. The papers are organized in the following topical sections: image quality assessment; image enhancement; image segmentation, registration and analysis; image coding, compression and encryption; dimensionality reduction and classification; biometrics; face description, detection and recognition; human activity recognition; robotics and 3D vision; medical image analysis; and applications.

• Machine Learning
• Medical Image and Analysis
• Analysis of Histopathology Images
• Diagnosis and Screening of Ophthalmic Diseases
• Grand Challenge on Automatic Lung Cancer Patient Management.

This two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020. The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management. Due to the corona pandemic, ICIAR 2020 was held virtually only.

• Feature Extraction, Computer Vision and Pattern Recognition
• Multispectral and Color Imaging
• Image Filtering, Segmentation and Super-Resolution
• Signal Processing
• Biomedical Imaging
• Geoscience and Remote Sensing
• Watermarking, Authentication and Coding
• 3d Acquisition, Processing and Applications.

This book constitutes the refereed proceedings of the 7th International Conference, ICISP 2016, held in May/June 2016 in Trois-Rivières, QC, Canada. The 40 revised full papers were carefully reviewed and selected from 83 submissions. The contributions are organized in topical sections on features extraction, computer vision, and pattern recognition; multispectral and color imaging; image filtering, segmentation, and super-resolution; signal processing; biomedical imaging; geoscience and remote sensing; watermarking, authentication and coding; and 3d acquisition, processing, and applications.