Synopsis
Presents recent developments in the classical and modern hybrid methodologies currently being applied in pattern recognition. The 21 chapters deal with decision theoretic classification using the statistical approach, neural networks, the fuzzy set approach, the use of genetic algorithms, and soft computing. Topics include Bayesian approaches for unsupervised classification, networks of spiking neurons in data mining, adaptive segmentation techniques for hyperspectral imagery, and writing speed and writing sequence invariant on-line handwriting recognition. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Review
Demonstrates the significance of this evolution relevance of different approaches with characteristic features and the formulation of various modern theorem. -- Zentralblatt MATH
This is a timely, comprehensive, and authoritative volume belonging to the mainstream of pattern recognition. -- Mathematical Reviews, 2003
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Pattern Recognition From Classical to Modern Approaches
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World Scientific Publishing Company, 2002
ISBN 10: 9810246846
ISBN 13: 9789810246846
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PATTERN RECOGNITION
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Pattern Recognition From Classical to Modern Approaches
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