Hybrid methods in pattern recognition (Series in machine perception and artificial intelligence - vol. 47)

The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system.Hybrid Methods in Pattern Recognition is a col...

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Bibliographic Details
Main Authors:	Bunke, H, Kandel, A
Format:	eBook Book
Language:	English
Published:	New Jersey World Scientific Publishing Co. Pte. Ltd 2002 World Scientific World Scientific Publishing Company WORLD SCIENTIFIC World Scientific Publishing
Edition:	1
Series:	Series in machine perception and artificial intelligence
Subjects:	Artificial Intelligence (Machine Learning, Neural Networks, Fuzzy Logic) Computer Science COMPUTERS Electrical & Electronic Engineering (Circuits & Systems, Communications, Control, Computer Engineering) Networking Neural Networks Neural networks (Computer science) Pattern recognition systems Robotics (Machine Vision, Pattern Recognition) Multiple Classifier System Fuzzy Systems Data Mining Clustering Fingerprint Identification Machine Learning Granular Computing Neural Network Pattern Recognition Neural Network Fusion Image Processing Soft Computing Hidden Markov Model Handwriting Recognition
ISBN:	9789810248321, 9810248326, 9812778144, 9789812778147
Online Access:	Get full text
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Table of Contents:

Hybrid methods in pattern recognition (Series in machine perception and artificial intelligence - vol. 47) -- Preface -- Contents -- Chapter 1: Fuzzification of Neural Networks for Classification Problems -- Chapter 2: Adaptive Graphic Pattern Recognition: Foundations and Perspectives -- Chapter 3: Adaptive Self-Organizing Map in the Graph Domain -- Chapter 4: From Numbers to Information Granules: A Study in Unsupervised Learning and Feature Analysis -- Chapter 5: Combination of Hidden Markov Models and Neural Networks for Hybrid Statistical Pattern Recognition -- Chapter 6: From Character to Sentences: A Hybrid Neuro-Markovian System for On-Line Handwriting Recognition -- Chapter 7: Multiple Classifier Combination: Lessons and Next Steps -- Chapter 8: Design of Multiple Classifier Systems -- Chapter 9: Fusing Neural Networks Through Fuzzy Integration -- Chapter 10: Hybrid Data Mining Methods in Image Processing -- Chapter 11: Robust Fingerprint Identification Based on Hybrid Pattern Recognition Methods -- Chapter 12: Text Categorization Using Learned Document Features.
Intro -- Contents -- Preface -- Neuro-Fuzzy Systems -- Chapter 1 Fuzzification of Neural Networks for Classification Problems -- Neural Networks for Structural Pattern Recognition -- Chapter 2 Adaptive Graphic Pattern Recognition: Foundations and Perspectives -- Chapter 3 Adaptive Self-Organizing Map in the Graph Domain -- Clustering for Hybrid Systems -- Chapter 4 From Numbers to Information Granules: A Study in Unsupervised Learning and Feature Analysis -- Combining Neural Networks and Hidden Markov Models -- Chapter 5 Combination of Hidden Markov Models and Neural Networks for Hybrid Statistical Pattern Recognition -- Chapter 6 From Character to Sentences: A Hybrid Neuro-Markovian System for On-Line Handwriting Recognition -- Multiple Classifier Systems -- Chapter 7 Multiple Classifier Combination: Lessons and Next Steps -- Chapter 8 Design of Multiple Classifier Systems -- Chapter 9 Fusing Neural Networks Through Fuzzy Integration -- Applications of Hybrid Systems -- Chapter 10 Hybrid Data Mining Methods in Image Processing -- Chapter 11 Robust Fingerprint Identification Based on Hybrid Pattern Recognition Methods -- Chapter 12 Text Categorization Using Learned Document Features