DocumentCode :
2261092
Title :
Absolute neuro-fuzzy classification of remote sensing data
Author :
Benediktsson, Jon Atli ; Benediktsson, Helgi ; Arnason, Kolbeinn
Author_Institution :
Eng. Res. Inst., Iceland Univ., Reykjavik, Iceland
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
969
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 are discussed and applied in classification of multisource remote sensing and geographic data. Both the rationale of the approaches and the results obtained are compared to more traditional techniques
Keywords :
fuzzy neural nets; fuzzy systems; genetic algorithms; geophysical signal processing; geophysical techniques; geophysics computing; image classification; neural nets; remote sensing; sensor fusion; terrain mapping; absolute neuro-fuzzy classification; decision making; derivative-free optimization; fuzzy inference; genetic algorithm; geophysical measurement technique; image classification; image processing; inferencing; intelligent system; knowledge; land surface; multisource remote sensing; neural net; neural network; remote sensing; sensor fusion; soft computing; terrain mapping; Computer networks; Decision making; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Humans; Hybrid intelligent systems; Neural networks; Pattern recognition; Remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-6359-0
Type :
conf
DOI :
10.1109/IGARSS.2000.857992
Filename :
857992
Link To Document :
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