Table of Contents
1 Cover
4 Abstract
5 Preface
6 1 Perception of Images. Modern Trends 1.1 Visual System 1.2 Eye. Types of Eye Movement 1.3 Perception of Figures and Background 1.4 Space Perception 1.5 Visual Illusions 1.6 Conclusion References
7 2 Image Recognition Based on Compositional Schemes 2.1 Artistic Image 2.2 Classification of Features 2.3 Compositional Analysis of an Art Work 2.4 Classification by Shape, Position, Color 2.5 Classification According to the Content of the Scenes 2.6 Compositional Analysis in Iconography 2.7 Associative Mechanism of Analysis 2.8 Conclusions References
8 3 Sensory and Project Images in the Design Practice 3.1 Sensory Image Nature 3.2 Language and Images Symbolics 3.3 Methods of Images Production in Ideas 3.4 Personality Image Projecting 3.5 Project Image 3.6 Conclusion References
9 4 Associative Perception of Conceptual Models of Exhibition Spaces 4.1 Associative Modeling of the Exhibition Space Environment 4.2 Associative Modeling of Environmental Objects in Exhibition Spaces 4.3 Conclusion References
10 5 Disentanglement For Discriminative Visual Recognition 5.1 Introduction 5.2 Problem Statement. Deep Metric Learning Based Disentanglement for FER 5.3 Adversarial Training Based Disentanglement 5.4 Methodology. Deep Metric Learning Based Disentanglement for FER 5.5 Adversarial Training Based Disentanglement 5.6 Experiments and Analysis 5.7 Discussion 5.8 Conclusion References
11 6 Development of the Toolkit to Process the Internet Memes Meant for the Modeling, Analysis, Monitoring and Management of Social Processes 6.1 Introduction 6.2 Modeling of Internet Memes Distribution 6.3 Intellectualization of System for Processing the Internet Meme Data Flow 6.4 Implementation of Intellectual System for Recognition of Internet Meme Data Flow 6.5 Conclusion References
12 7 The Use of the Mathematical Apparatus of Spatial Granulation in The Problems of Perception and Image Recognition 7.1 Introduction 7.2 The Image Processing and Analysis Base Conceptions 7.3 Human Visual Perception Modeling 7.4 Mathematic Modeling of Different Kinds of Digital Images 7.5 Zadeh’s Information Granulation Theory 7.6 Fundamentals of Spatial Granulation 7.7 Entropy-Preserved Granulation of Spatial Data 7.8 Digital Images Granulation Algorithms 7.9 Spatial Granulation Technique Applications 7.10 Conclusions References
13
8 Inverse Synthetic Aperture Radars: Geometry, Signal Models and Image Reconstruction Methods
8.1