Pattern Recognition: From Classical To Modern Approaches
eBook - PDF

Pattern Recognition: From Classical To Modern Approaches

From Classical to Modern Approaches

  1. 636 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Pattern Recognition: From Classical To Modern Approaches

From Classical to Modern Approaches

Book details
Table of contents
Citations

About This Book

This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource.

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Yes, you can access Pattern Recognition: From Classical To Modern Approaches by Sankar Kumar Pal, Amita Pal in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Vision & Pattern Recognition. We have over one million books available in our catalogue for you to explore.

Information

Publisher
World Scientific
Year
2001
ISBN
9789812386533
Topic
Computer Science
Subtopic
Computer Vision & Pattern Recognition
Index
Computer Science

Table of contents

  1. Foreword
  2. Preface
  3. Contents
  4. Chapter 1 PATTERN RECOGNITION: EVOLUTION OF METHODOLOGIES AND DATA MINING
  5. Chapter 2 IMPERFECT SUPERVISION IN STATISTICAL PATTERN RECOGNITION
  6. Chapter 3 ADAPTIVE STOCHASTIC ALGORITHMS FOR PATTERN CLASSIFICATION
  7. Chapter 4 UNSUPERVISED CLASSIFICATION: SOME BAYESIAN APPROACHES
  8. Chapter 5 SHAPE IN IMAGES
  9. Chapter 6 DECISION TREES FOR CLASSIFICATION : A REVIEW AND SOME NEW RESULTS
  10. Chapter 7 SYNTACTIC PATTERN RECOGNITION
  11. Chapter 8 FUZZY SETS AS A LOGIC CANVAS FOR PATTERN RECOGNITION
  12. Chapter 9 FUZZY PATTERN RECOGNITION BY FUZZY INTEGRALS AND FUZZY RULES
  13. Chapter 10 NEURAL NETWORK BASED PATTERN RECOGNITION
  14. Chapter 11 PATTERN CLASSIFICATION BASED ON QUANTUM NEURAL NETWORKS: A CASE STUDY
  15. Chapter 12 NETWORKS OF SPIKING NEURONS IN DATA MINING
  16. Chapter 13 GENETIC ALGORITHMS, PATTERN CLASSIFICATION AND NEURAL NETWORKS DESIGN
  17. Chapter 14 ROUGH SETS IN PATTERN RECOGNITION
  18. Chapter 15 COMBINING CLASSIFIERS: SOFT COMPUTING SOLUTIONS
  19. Chapter 16 AUTOMATED GENERATION OF QUALITATIVE REPRESENTATIONS OF COMPLEX OBJECTS BY HYBRID SOFT-COMPUTING METHODS
  20. Chapter 17 NEURO-FUZZY MODELS FOR FEATURE SELECTION AND CLASSIFICATION
  21. Chapter 18 ADAPTIVE SEGMENTATION TECHNIQUES FOR HYPERSPECTRAL IMAGERY
  22. Chapter 19 PATTERN RECOGNITION ISSUES IN SPEECH PROCESSING
  23. Chapter 20 WRITING SPEED AND WRITING SEQUENCE INVARIANT ON-LINE HANDWRITING RECOGNITION
  24. Chapter 21 TONGUE DIAGNOSIS BASED ON BIOMETRIC PATTERN RECOGNITION TECHNOLOGY
  25. Index
  26. About the Editors