Pattern Recognition and Artificial Intelligence

Author: Chen   C. H.  

Publisher: Elsevier Science‎

Publication year: 2013

E-ISBN: 9780323144209

P-ISBN(Paperback): 9780121709501

P-ISBN(Hardback):  9780121709501

Subject:

Language: ENG

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Description

Pattern Recognition and Artificial Intelligence contains the proceedings of the Joint Workshop on Pattern Recognition and Artificial Intelligence held in Hyannis, Massachusetts, on June 1-3, 1976. The papers explore developments in pattern recognition and artificial intelligence and cover topics ranging from scene analysis and data structure to syntactic methods, biomedicine, speech recognition, game-playing programs, and computer graphics. Grammar inference methods, image segmentation and interpretation, and relational databases are also discussed.
This book is comprised of 29 chapters and begins with a description of a data structure that can learn simple programs from training samples. The reader is then introduced to the syntactic parts of pattern recognition systems; methods for multidimensional grammatical inference; a scene analysis system capable of finding structure in outdoor scenes; and a language called DEDUCE for relational databases. A sculptor's studio-like environment, in which the ""sculptor"" can create complex three-dimensional objects in the computer similar to molding a piece of clay in the machine, is also described. The remaining chapters focus on statistical and structural feature extraction; use of maximum likelihood functions for recognition of highly variable line drawings; region extraction using boundary following; and interactive screening of reconnaissance imagery.
This monograph will be of interest to engineers, graduate students, and

Chapter

Front Cover

pp.:  1 – 4

Copyright Page

pp.:  5 – 6

Table of Contents

pp.:  6 – 8

LIST OF CONTRIBUTORS

pp.:  8 – 10

PREFACE

pp.:  10 – 12

CHAPTER 3. SOME MULTIDIMENSIONAL GRAMMAR INFERENCE METHODS

pp.:  40 – 72

CHAPTER 4. FINDING STRUCTURE IN OUTDOOR SCENES

pp.:  72 – 97

CHAPTER 5. MOLDING COMPUTER CLAY - STEPS TOWARD A COMPUTER GRAPHICS SCULPTORS' STUDIO

pp.:  97 – 119

CHAPTER 6. DEDUCE --- A DEDUCTIVE QUERY LANGUAGE FOR RELATIONAL DATA BASES

pp.:  119 – 146

CHAPTER 7. ON STATISTICAL AND STRUCTURAL FEATURE EXTRACTION

pp.:  146 – 156

CHAPTER 8. ON THE RECOGNITION OF HIGHLY VARIABLE LINE DRAWINGS THROUGH USE OF MAXIMUM LIKELIHOOD FUNCTIONS

pp.:  156 – 175

CHAPTER 9. A MINICOMPUTER BASED REAL TIME EYE TRACKING SYSTEM FOR PATTERN RECOGNITION APPLICATIONS

pp.:  175 – 196

CHAPTER 10. DESIGN OF OPTIMAL FEATURE EXTRACTORS BY MATHEMATICAL PROGRAMMING TECHNIQUES

pp.:  196 – 206

CHAPTER 11. TYPOLOGICAL SELECTION OF PARAMETERS

pp.:  206 – 227

CHAPTER 12. REGION EXTRACTION USING BOUNDARY FOLLOWING

pp.:  227 – 244

CHAPTER 13. COMPUTER-AIDED DIAGNOSIS OF BREAST CANCER FROM THERMOGRAPHY

pp.:  244 – 259

CHAPTER 14. STRUCTURAL ISOMORPHISM OF PICTURE GRAPHS

pp.:  259 – 268

CHAPTER 15. TREE LANGUAGES AND SYNTACTIC PATTERN RECOGNITION

pp.:  268 – 303

CHAPTER 16. ACQUISITION AND UTILIZATION OF ACCESS PATTERNS IN RELATIONAL DATA BASE IMPLEMENTATION

pp.:  303 – 325

CHAPTER 17. PATTERNS OF INDUCTION AND ASSOCIATED KNOWLEDGE ACQUISTION ALGORITHMS

pp.:  325 – 351

CHAPTER 18. PICTORIAL MEDICAL PATTERN RECOGNITION

pp.:  351 – 385

CHAPTER 19. DISTANCE MEASURES FOR SPEECH RECOGNITION - PSYCHOLOGICAL AND INSTRUMENTAL

pp.:  385 – 400

CHAPTER 20. SYNTACTIC PATTERN RECOGNITION ON THE BASIS OF FUNCTIONAL APPROXIMATION

pp.:  400 – 410

CHAPTER 21. A PROGRAM FOR LEARNING TO PLAY CHESS

pp.:  410 – 431

CHAPTER 22. INTERACTIVE SCREENING OF RECONNAISSANCE IMAGERY

pp.:  431 – 463

CHAPTER 23. AN ICONIC/SYMBOLIC DATA STRUCTURING SCHEME

pp.:  463 – 483

CHAPTER 24. IGS: A PARADIGM FOR INTEGRATING IMAGE SEGMENTATION AND INTERPRETATION

pp.:  483 – 519

CHAPTER 25. PATTERN RECOGNITION USING DEGENERATE REFERENCE DATA

pp.:  519 – 540

CHAPTER 26. SERIAL PATTERN ACQUISITION: A PRODUCTION SYSTEM APPROACH

pp.:  540 – 565

CHAPTER 27. DABI—A DATA BASE FOR IMAGE ANALYSIS WITH NONDETERMINISTIC INFERENCE CAPABILITY

pp.:  565 – 587

CHAPTER 28. APPENDIX A. EXAMPLE OF A GENERIC MODEL

pp.:  587 – 604

CHAPTER 29. RELAXATION LABELLING. LOCAL AMBIGUITY, AND LOW-LEVEL VISION

pp.:  604 – 628

SUBJECT INDEX

pp.:  628 – 633

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