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Proceedings Paper

Adaptive learning concepts and methodology for enhanced recognition system performance
Author(s): Belur V. Dasarathy
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Paper Abstract

This study presents innovative adaptive learning concepts and resulting methodology designed for enhancing the performance of recognition systems such as automatic target recognition (ATR) systems wherein robustness of performance is a significant issue. The basic underlying concept is that of learning in partially exposed environments, wherein the system is not necessarily aware of all the pattern classes that may be encountered in the operational phase. The methodology is based on such learning as required by nearest neighbor based decision systems. The paper discusses several stages of sophistication of the system design and illustrates these with two sets of numerical experiments (using the now classical iris data as well as some real-world TV image data) to bring out the subtleties of the issues involved.

Paper Details

Date Published: 29 July 1994
PDF: 12 pages
Proc. SPIE 2234, Automatic Object Recognition IV, (29 July 1994); doi: 10.1117/12.181034
Show Author Affiliations
Belur V. Dasarathy, Dynetics, Inc. (United States)

Published in SPIE Proceedings Vol. 2234:
Automatic Object Recognition IV
Firooz A. Sadjadi, Editor(s)

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