Application of a vision neural network in an automatic target recognition system

James G. Landowski; Baldamar Gil

doi:10.1117/12.140026

16 September 1992 Application of a vision neural network in an automatic target recognition system

James G. Landowski, Baldamar Gil

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.140026
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

This paper describes the application of a visual pattern recognition neural network in a hybrid model based automatic target recognition (ATR) system. This neural network forms the feature extraction front end of the ATR and is derived from the Neocognitron network first proposed by K. Fukushima. For complex target recognition, modifications to the basic Neocognitron network paradigm were required to enhance robustness against image distortions due to undersampling (aliasing) and poor feature selection during training. The focus of the paper is on the enhancements, their rationale, and on the use of the network as a self- organizing feature extraction element of an ATR. Results of experiments with the overall ATR system against target imagery are shown and discussed.

Citation Download Citation

James G. Landowski and Baldamar Gil "Application of a vision neural network in an automatic target recognition system", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140026

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