Artificial Neural Networks for Pattern Recognition

Steven K. Rogers; Dennis W. Ruck; Matthew Kabrisky; Gregory L. Tarr

doi:10.1117/12.969754

1 March 1990 Artificial Neural Networks for Pattern Recognition

Steven K. Rogers, Dennis W. Ruck, Matthew Kabrisky, Gregory L. Tarr

Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969754
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

A three unit artificial neural network (ANN) automatic target recognition (ATR) system is integrated within, and compared to, a recently AFIT developed conventional ATR system. The integration of ANN within this existing framework allows the determination of where the benefits of using these biologically motivated processing techniques lie. The integration and testing of ANN within each of the three units constitutes the major contribution of this research. The emphasis of this paper is in the area of effects of learning alternatives on ATR. Several alternative feedforward networks were compared in the classifier unit.

Citation Download Citation

Steven K. Rogers, Dennis W. Ruck, Matthew Kabrisky, and Gregory L. Tarr "Artificial Neural Networks for Pattern Recognition", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); https://doi.org/10.1117/12.969754

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