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Proceedings Paper

New distortion-invariant SVRDM hierarchical classifier
Author(s): David P. Casasent; Yu-Chiang Wang
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Paper Abstract

A hierarchical classifier using a new SVRDM (support vector representation and discrimination machine) is proposed for automatic target recognition. Shift and scale-invariant features are considered. In addition, we consider the ability of the classifier to reject non-object class or clutter inputs. Initial recognition and rejection test results on infra-red (IR) data are excellent.

Paper Details

Date Published: 25 October 2004
PDF: 9 pages
Proc. SPIE 5608, Intelligent Robots and Computer Vision XXII: Algorithms, Techniques, and Active Vision, (25 October 2004); doi: 10.1117/12.593037
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Yu-Chiang Wang, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 5608:
Intelligent Robots and Computer Vision XXII: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Roning, Editor(s)

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