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Proceedings Paper

Hybrid fuzzy-neural classifier for feature level data fusion in ladar autonomous target recognition
Author(s): Stephen Soliday; Melissa Tay Perona; Daniel G. McCauley
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Paper Abstract

This paper will discuss the design of a hybrid fuzzy-neural classifier for fusion of range and intensity channels coming from a LADAR sensor. Fusion was performed on a feature rather than pixel level. Results will be compared between ATR performance with and with out fusion. Also, discussed in this paper is the use of genetic algorithms for the training and optimization of the ATR system with a limited set of ground truth.

Paper Details

Date Published: 22 October 2001
PDF: 12 pages
Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); doi: 10.1117/12.445409
Show Author Affiliations
Stephen Soliday, Raytheon Information Systems (United States)
Melissa Tay Perona, Raytheon Missile Systems (United States)
Daniel G. McCauley, Raytheon Electronic Systems (United States)

Published in SPIE Proceedings Vol. 4379:
Automatic Target Recognition XI
Firooz A. Sadjadi, Editor(s)

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