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Pattern Recognition Theory and Applications pp 367–382Cite as

Hybrid Methods in Pattern Recognition

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Part of the book series: NATO ASI Series ((NATO ASI F,volume 30))

Abstract

The field of pattern recognition has grown enormously in recent years and a wide variety of techniques have been developed for various applications. Traditionally, these techniques can be categorized into statistical, or decision theoretic, and structural methods. Additionally, artificial intelligence based approaches have become very important recently. Each of the different methods has its strength and its limitations. For overcoming these limitations, statistical, structural, and artificial intelligence based methods are mixed sometimes. This results in a hybrid approach.

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Author information

Authors and Affiliations

  1. Institut für Informatik und angewandte Mathematik, Universität Bern, Länggassstrasse 51, CH-3012, Bern, Switzerland

    Horst Bunke

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  1. Horst Bunke
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Editors and Affiliations

  1. Philips Research Laboratory, Avenue Em. Van Becelaere 2, Box 8, B-1170, Brussels, Belgium

    Pierre A. Devijver

  2. Department of Electronic and Electrical Engineering, University of Surrey, GU2 5XH, Guildford, UK

    Josef Kittler

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© 1987 Springer-Verlag Berlin Heidelberg

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Bunke, H. (1987). Hybrid Methods in Pattern Recognition. In: Devijver, P.A., Kittler, J. (eds) Pattern Recognition Theory and Applications. NATO ASI Series, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83069-3_29

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  • DOI: https://doi.org/10.1007/978-3-642-83069-3_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-83071-6

  • Online ISBN: 978-3-642-83069-3

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