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Proceedings Paper

Continuous recognition of sonar targets using neural networks
Author(s): Kootala P. Venugopal; Abhijit S. Pandya; Raghavan Sudhakar
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Paper Abstract

A neural network (NN) approach for the continuous recognition of undersea targets from side- scan sonar returns is presented. This approach takes more than one return at a time, thereby enabling the network to learn the spectral temporal dependencies of consecutive returns. The horizontal distance scanned at a time could be expanded by increasing the number of groups in the input layer of the network. Also, a simple and powerful stochastic algorithm called Alopex is described for the training of the network. The studies and results with approach are described.

Paper Details

Date Published: 1 August 1991
PDF: 10 pages
Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); doi: 10.1117/12.44865
Show Author Affiliations
Kootala P. Venugopal, Florida Atlantic Univ. (United States)
Abhijit S. Pandya, Florida Atlantic Univ. (United States)
Raghavan Sudhakar, Florida Atlantic Univ. (United States)

Published in SPIE Proceedings Vol. 1471:
Automatic Object Recognition
Firooz A. Sadjadi, Editor(s)

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