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Proceedings Paper

Neural networks, recognition based on differences
Author(s): Jacek Mandziuk
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Paper Abstract

The concept of similarity is fundamental to pattern recognition and associative memories. In recent years many mathematical models with various neural network struc- tures and different learning algorithms have been proposed. Generally in these mo- dels, the neural network emphasizes the association within the stored objects, and such models are quite effective under the assumption that the stored objects signifi- cantly differ from one another (are independent)1. Unfortunately, in practice, the objects are usually not independent, moreover, the differences among the patterns are often very small, and recognition methods based on the similar features fail. Having a number of similar objects, for example human faces, with many features identical, what features do we use to recognize a particular individual?

Paper Details

Date Published: 26 July 1993
PDF: 2 pages
Proc. SPIE 1983, 16th Congress of the International Commission for Optics: Optics as a Key to High Technology, 19835D (26 July 1993); doi: 10.1117/12.2308612
Show Author Affiliations
Jacek Mandziuk, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 1983:
16th Congress of the International Commission for Optics: Optics as a Key to High Technology
Gyorgy Akos; Tivadar Lippenyi; Gabor Lupkovics; Andras Podmaniczky, Editor(s)

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