DocumentCode :
381224
Title :
Remote sensing images classification using fuzzy B-spline function neural network
Author :
Mao, Jianxu ; Wang, Yaonan ; Sun, Wei
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Volume :
3
fYear :
2002
fDate :
2002
Firstpage :
2159
Abstract :
We propose a remote sensing image classification algorithm using the membership function adjustable fuzzy B-spline function neural network. In the proposed classification algorithm, the fuzzy technique and neural network technique are combined, and fuzzy inference is realized by a neural network. The B-spline function is used as the membership function of the fuzzy neural network and its shape can be adjusted in real time, which endows the classifier with better capability of learning and self-adaptiveness. Experimental results show that the proposed classification algorithm can be used in remote sensing image classification, and its classification precision is superior to that of the conventional maximum likelihood algorithm.
Keywords :
fuzzy neural nets; image classification; inference mechanisms; learning (artificial intelligence); real-time systems; remote sensing; splines (mathematics); uncertainty handling; experimental results; fuzzy B-spline function neural network; fuzzy inference; learning; maximum likelihood algorithm; membership function; real time; remote sensing image classification; self-adaptive system; Classification algorithms; Fuzzy control; Fuzzy neural networks; Image classification; Inference algorithms; Neural networks; Remote sensing; Shape control; Space technology; Spline;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
Type :
conf
DOI :
10.1109/WCICA.2002.1021468
Filename :
1021468
Link To Document :
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