Neuro-fuzzy and soft computing in classification of remote sensing data

Jon Atli Benediktsson; Helgi Benediktsson

doi:10.1117/12.373255

14 December 1999 Neuro-fuzzy and soft computing in classification of remote sensing data

Jon Atli Benediktsson, Helgi Benediktsson

Proceedings Volume 3871, Image and Signal Processing for Remote Sensing V; (1999) https://doi.org/10.1117/12.373255
Event: Remote Sensing, 1999, Florence, Italy

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.

Citation Download Citation

Jon Atli Benediktsson and Helgi Benediktsson "Neuro-fuzzy and soft computing in classification of remote sensing data", Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); https://doi.org/10.1117/12.373255

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