Detection and classification of buried dielectric anomalies by means of the bispectrum method and neural networks
Date
1995
Authors
Balan, Ajay, N., author
Azimi-Sadjadi, Mahmood R., author
IEEE, publisher
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Abstract
The development of neural network-based system for detection and classification of buried landmines is the main focus of this paper. Shape-dependent features are extracted by means of the bispectrum method. These features are then applied to the neural network. A multilayer back-propagation-type neural network is trained and tested on the feature sets extracted from equally spaced radial slices of image windows. Simulation results obtained for two types of targets indicated good detection and classification rates.
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Rights Access
Subject
multilayer perceptrons
military systems
feature extraction
feedforward neural nets