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A hierarchical classifier using new support vector machines for automatic target recognition
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DOI：10.1016/j.neunet.2005.06.033.png)
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Abstract
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A binary hierarchical classifier is proposed for automatic target recognition. We also require rejection of non-object (non-target) inputs, which are not seen during training or validation, thus producing a very difficult problem. The SVRDM (support vector representation and discrimination machine) classifier is used at each node in the hierarchy, since it offers good generalization and rejection ability. Using this hierarchical SVRDM classifier with magnitude Fourier transform (vertical bar FT vertical bar) features, which provide shift-invariance, initial test results on infrared (IR) data are excellent. (c) 2005 Elsevier Ltd. All rights reserved.
Keywords:
automatic target recognition
hierarchical classifier
support vector machine
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