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Proceedings Paper

Rejection of unfamiliar patterns with multilayer neural networks
Author(s): Behrooz Kamgar-Parsi; Behzad Kamgar-Parsi
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Paper Abstract

Most of the pattern recognition applications of multilayer neural networks have been concerned with classification and not rejection of a given pattern. For example, in character recognition all alphabetical characters must be recognized as one of the 26 characters, as there is nothing to reject. However, in many situations, there is no guarantee that all the patterns that will be presented to the network would actually belong to one of the classes on which the network has been trained. In such cases, a useful network must be capable of rejection as well as classification. In this paper we propose a scheme to develop multilayer networks with rejection capabilities. The discriminating power of the proposed technique appears to be comparable to that of the human eye.

Paper Details

Date Published: 6 April 1995
PDF: 15 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205153
Show Author Affiliations
Behrooz Kamgar-Parsi, Naval Research Lab. (United States)
Behzad Kamgar-Parsi, Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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