Statistical and Neural Classifiers - An Integrated Approach to Design (Hardcover, 2001 ed.)

The classification of patterns is an important area of research which is central to all pattern recognition fields, including speech, image, robotics, and data analysis. Neural networks have been used successfully in a number of these fields, but so far their application has been based on a "black box approach", with no real understanding of how they work.In this book, Sarunas Raudys - an internationally respected researcher in the area - provides an excellent mathematical and applied introduction to how neural network classifiers work and how they should be used to optimal effect. Among the topics covered are:- Different types of neural network classifiers;- A taxonomy of pattern classification algorithms;- Performance capabilities and measurement procedures;- Which features should be extracted from raw data for the best classification results.This book will provide essential reading for anyone researching or studying relevant areas of pattern recognition (such as image processing, speech recognition, robotics, and multimedia). It will also be of interest to anyone studing or researching in applied neural networks.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Series:	Advances in Computer Vision and Pattern Recognition
Release date:	2001
First published:	2001
Authors:	Sarunas Raudys
Dimensions:	234 x 156 x 19mm (L x W x T)
Format:	Hardcover
Pages:	295
Edition:	2001 ed.
ISBN-13:	978-1-85233-297-6
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Promotions
LSN:	1-85233-297-2
Barcode:	9781852332976

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