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Proceedings Paper

Neural network technology for automatic target recognition
Author(s): Michael W. Roth
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Paper Abstract

A brief review is presented of neural network tools for Automatic Target Recognition (ATR) . These tools include collective computation for implementing a variety of computational-vision techniques learning and adaptation for pattern recognition knowledge integration for expert-system capabilities and beyondsupercomputer- level hardware. As a specific example neural networks for stereo vision are introduced as a potentially fruitful approach to ATR. Preliminary results are presented which show substantial performance improvements over previous stereo algorithms for producing accurate dense displacement maps. These maps can be used in turn to derive accurate geometrical shape information that can result in improved recognition performance. 1.

Paper Details

Date Published: 1 August 1990
PDF: 12 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21157
Show Author Affiliations
Michael W. Roth, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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