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Proceedings Paper

Neuro-fuzzy and soft computing in classification of remote sensing data
Author(s): Jon Atli Benediktsson; Helgi Benediktsson
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Paper Abstract

Hybrid intelligent systems are discussed. These systems combine neural networks, which recognize patterns and adapt themselves to cope with changing environments, and fuzzy inference systems that incorporate human knowledge and perform inferencing and decision making. The integration of these complimentary techniques along with derivative-free optimization techniques based on genetic algorithms, results in a novel discipline called neuro-fuzzy and soft computing. These approaches will be discussed and applied in classification of multisource remote sensing and geographic data. Both the rationale of the approaches and the results obtained by the methods will be compared to more traditional techniques.

Paper Details

Date Published: 14 December 1999
PDF: 12 pages
Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); doi: 10.1117/12.373255
Show Author Affiliations
Jon Atli Benediktsson, Univ. of Iceland (Iceland)
Helgi Benediktsson, Univ. of Iceland (Iceland)

Published in SPIE Proceedings Vol. 3871:
Image and Signal Processing for Remote Sensing V
Sebastiano Bruno Serpico, Editor(s)

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