JOURNAL ARTICLE

<title>Neural network technology for automatic target recognition</title>

Michal Roth

Year: 1990 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Pages: 65-76   Publisher: SPIE

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.

Keywords:
Computer science Artificial neural network Artificial intelligence Computation Automatic target recognition Adaptation (eye) Variety (cybernetics) Computer vision Pattern recognition (psychology) Algorithm

Metrics

5
Cited By
1.00
FWCI (Field Weighted Citation Impact)
0
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

3D Surveying and Cultural Heritage
Physical Sciences →  Earth and Planetary Sciences →  Geology
Optical measurement and interference techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Satellite Image Processing and Photogrammetry
Physical Sciences →  Engineering →  Ocean Engineering

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