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Proceedings Paper

Neural network classifiers in target detection
Author(s): Hal E. Beck; Ruey Y. Han; Herbert A. Duvoisin; Joe R. Brown
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Paper Abstract

The focus of this paper is on the classifier module for a real-time automatic target recognition system. It is a dynamic neural network that utilizes adaptive, on-line learning. The on-line learning component is required because of the changeability of the target detection scenario resulting in unpredictable feature space representation of targets and clutter. The system was successfully tested against IR imagery of target models.

Paper Details

Date Published: 16 September 1992
PDF: 4 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.139972
Show Author Affiliations
Hal E. Beck, Univ. of Tennessee/Knoxville (United States)
Ruey Y. Han, Martin Marietta Corp. (United States)
Herbert A. Duvoisin, Martin Marietta Corp. (United States)
Joe R. Brown, Microelectronics and Computer Technology Corp. (United States)

Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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