Pattern Recognition Techniques, Technology and Applications

A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process.

Book Description

Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition.

Table of Contents

• Local Energy Variability as a Generic Measure of Bottom-Up Salience
• Real-Time Detection of Infrared Profile Patterns and Features Extraction
• A Survey of Shape Feature Extraction Techniques
• Computational Intelligence Approaches to Brain Signal Pattern Recognition
• Automatic Calibration of Hybrid Dynamic Vision System for High Resolution Object Tracking
• Image Representation Using Fuzzy Morphological Wavelet
• Multidimensional Texture Analysis for Unsupervised Pattern Classification
• Rock Particle Image Segmentation and Systems
• Unsupervised Texture Segmentation
• Optimization of Goal Function Pseudogradient in the Problem of Interframe Geometrical Deformations Estimation
• New Digital Approach to CNN On-chip Implementation for Pattern Recognition
• Distortion-Invariant Pattern Recognition with Adaptive Correlation Filters
• Manifold Matching for High-Dimensional Pattern Recognition
• Output Coding Methods: Review and Experimental Comparison
• Activity Recognition Using Probabilistic Timed Automata
• Load Time-Series Classification Based on Pattern Recognition Methods
• Theory of Cognitive Pattern Recognition
• Parametric Circle Approximation Using Genetic Algorithms
• Registration of Point Patterns Using Modern Evolutionary Algorithms
• Investigation of a New Artificial Immune System Model Applied to Pattern Recognition
• Designing a Pattern Recognition Neural Network with a Reject Output and Many Sets of Weights and Biases
• A Hybrid Pattern Recognition Architecture for Cutting Tool Condition Monitoring
• Mining Digital Music Score Collections: Melody Extraction and Genre Recognition
• Application of Forward Error Correcting Algorithms to Positioning Systems
• Pattern Recognition in Time-Frequency Domain: Selective Regional Correlation and Its Applications

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