Literature DB >> 16087318

A hierarchical classifier using new support vector machines for automatic target recognition.

David Casasent1, Yu-Chiang Wang.   

Abstract

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 (|FT|) features, which provide shift-invariance, initial test results on infra-red (IR) data are excellent.

Mesh:

Year:  2005        PMID: 16087318     DOI: 10.1016/j.neunet.2005.06.033

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  1 in total

1.  3D multi-parametric breast MRI segmentation using hierarchical support vector machine with coil sensitivity correction.

Authors:  Yi Wang; Glen Morrell; Marta E Heibrun; Allison Payne; Dennis L Parker
Journal:  Acad Radiol       Date:  2012-10-23       Impact factor: 3.173

  1 in total

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