DocumentCode
2982264
Title
Remote Sensing Image in Mining Area Classification Based on LVQ2 Neural Network
Author
Hu, Youjian ; Luo, Hongxia
Author_Institution
Fac. of Inf. Enginerring, China Univ. of Geosci. (Wuhan) CUG, Wuhan, China
fYear
2010
fDate
25-27 June 2010
Firstpage
1551
Lastpage
1553
Abstract
The remote sensing shows a widest perspective for land reclamation in mining areas. Based on how to improve the classification accuracy of mine image, we did some classification researchs with LVQ2 neural network. The proposed method had been applied to the aerial image of Heng country, Guangxi Province. The total classification accuracy was 72%, comparing with the minimum distance method increased by 9%.
Keywords
geophysical image processing; image classification; learning (artificial intelligence); mining; neural nets; remote sensing; vector quantisation; LVQ2 neural network; aerial image; classification accuracy; land reclamation; mine image; minimum distance method; mining area classification; remote sensing image; Accuracy; Artificial neural networks; Classification algorithms; Geology; Image classification; Remote sensing; Signal processing algorithms; LVQ2; mining area; neural network; remote sensing image classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6880-5
Type
conf
DOI
10.1109/iCECE.2010.382
Filename
5630000
Link To Document