Written by world-renowned authors, this unique compendium presents the most updated progress in pattern recognition and computer vision (PRCV), fully reflecting the strong international research interests in the artificial intelligence arena. Machine learning has been the key to current developments in PRCV. This useful comprehensive volume complements the previous five editions of the book. It places great emphasis on the use of deep learning in many aspects of PRCV applications, not readily available in other reference text.

Table of Contents

PART 1: THEORY, TECHNOLOGY AND SYSTEMS

A Brief Introduction to Part 1 (by C.H. Chen)

Chapter 1.1 Optimal Statistical Classification

Chapter 1.2 Deep Discriminative Feature Learning Method for Object Recognition

Chapter 1.3 Deep Learning Based Background Subtraction: A Systematic Survey

Chapter 1.4 Similarity Domains Network for Modeling Shapes and Extracting Skeletons without Large Datasets

Chapter 1.5 On Curvelet-Based Texture Features for Pattern Classification (Reprinted from Chapter 1.7 of 5th H BPRCV)

Chapter 1.6 An Overview of Efficient Deep Learning on Embedded Systems

Chapter 1.7 Random Forest for Dissimilarity-Based Multi-View Learning

Chapter 1.8 A Review of Image Colourisation

Chapter 1.9 Recent Progress of Deep learning for Speech Recognition

PART 2: APPLICATIONS

A Brief Introduction to Part 2 (by C.H. Chen)

Chapter 2.1 Machine Learning in Remote Sensing

Chapter 2.2 Hyperspectral and Spatially Adaptive Unmixing for Analytical Reconstruction of Fraction Surfaces from Data with Corrupt Pixels

Chapter 2.3 Image Processing for Sea Ice Parameter Identification from Visual Images

Chapter 2.4 Applications of Deep Learning to Brain Segmentation and Labeling of MRI Brain Structures

Chapter 2.5 Automatic Segmentation of IVUS Images Based on Temporal Texture Analysis

Chapter 2.6 Deep Learning for Historical Document Analysis

Chapter 2.7 Signature Verification via Graph-Based Methods

Chapter 2.8 Cellular Neural Network for Seismic Pattern Recognition

Chapter 2.9 Incorporating Facial Attributes in Cross-modal Face Verification and Synthesis

Chapter 2.10 Connected and Autonomous Vehicles in the Deep Learning Era: A Case Study on Computer-Guided Steering