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18 October 2001 Comparison of two classifier training methodologies for underwater mine detection/classification
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We describe here the current form of Alphatech's image processing and neural network based algorithms for detection and classification of mines in side-scan sonar imagery, and results obtained form their application to three distinct databases. In particular, we contrast here results obtained from the use of a currently employed 'baseline' multilayer perceptron classifier training approach, with the use of a state of the art commercial neural network package, NeuralSIM, developed by Neuralware, Inc.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Martin G. Bello "Comparison of two classifier training methodologies for underwater mine detection/classification", Proc. SPIE 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI, (18 October 2001);

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