DocumentCode :
1950446
Title :
An Application of Neuro-fuzzy System in Remote Sensing Image Classification
Author :
Wei, Wu ; Guanglai, Gao
Author_Institution :
Comput. Sci. Dept., Inner Mongolia Univ., Huhhot
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
1069
Lastpage :
1072
Abstract :
This paper introduces a classification algorithm-NEFCLASS (neuro-fuzzy classification) to classify remote sensing images landsat7 etm+. The NEFCLASS combines neural networks and fuzzy systems to learn from the training data and generate conditional linguistic rules. Then we use the rules to classify the land-cover/land-use classes in landsat7 etm+ images covering main Bayannaoer city of Inner Mongolia Autonomous Region selected in August 2007. Compared to the ground truth, the experiment result shows that the overall classification accuracy can achieve to 79.93%.
Keywords :
fuzzy neural nets; image classification; learning (artificial intelligence); remote sensing; conditional linguistic rules; neurofuzzy classification; remote sensing image classification; Biological neural networks; Computer science; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Image classification; Remote sensing; Satellites; Training data; classification; neuro-fuzzy; remote sensing images;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.1222
Filename :
4721937
Link To Document :
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