Pattern Recognition
eBook - PDF

Pattern Recognition

Techniques, Technology and Applications

  1. 638 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Pattern Recognition

Techniques, Technology and Applications

About this book

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

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Yes, you can access Pattern Recognition by Peng-Yeng Yin in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Pattern Recognition Techniques, Technology and Applications
  2. Preface
  3. Contents
  4. 1. Local Energy Variability as a Generic Measure of Bottom-Up Salience
  5. 2. Real-Time Detection of Infrared Profile Patterns and Features Extraction
  6. 3. A Survey of Shape Feature Extraction Techniques
  7. 4. Computational Intelligence Approaches to Brain Signal Pattern Recognition
  8. 5. Automatic Calibration of Hybrid Dynamic Vision System for High Resolution Object Tracking
  9. 6. Image Representation Using Fuzzy Morphological Wavelet
  10. 7. Multidimensional Texture Analysis for Unsupervised Pattern Classification
  11. 8. Rock Particle Image Segmentation and Systems
  12. 9. Unsupervised Texture Segmentation
  13. 10. Optimization of Goal Function Pseudogradient in the Problem of Interframe Geometrical Deformations Estimation
  14. 11. New Digital Approach to CNN On-chip Implementation for Pattern Recognition
  15. 12. Distortion-Invariant Pattern Recognition with Adaptive Correlation Filters
  16. 13. Manifold Matching for High-Dimensional Pattern Recognition
  17. 14. Output Coding Methods: Review and Experimental Comparison
  18. 15. Activity Recognition Using Probabilistic Timed Automata
  19. 16. Load Time-Series Classification Based on Pattern Recognition Methods
  20. 17. Theory of Cognitive Pattern Recognition
  21. 18. Parametric Circle Approximation Using Genetic Algorithms
  22. 19. Registration of Point Patterns Using Modern Evolutionary Algorithms
  23. 20. Investigation of a New Artificial Immune System Model Applied to Pattern Recognition
  24. 21. Designing a Pattern Recognition Neural Network with a Reject Output and Many Sets of Weights and Biases
  25. 22. A SIFT-Based Fingerprint Verification System Using Cellular Neural Networks
  26. 23. The Fourth Biometric - Vein Recognition
  27. 24. A Hybrid Pattern Recognition Architecture for Cutting Tool Condition Monitoring
  28. 25. Mining Digital Music Score Collections: Melody Extraction and Genre Recognition
  29. 26. Application of Forward Error Correcting Algorithms to Positioning Systems
  30. 27. Pattern Recognition in Time-Frequency Domain: Selective Regional Correlation andIts Applications