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《Journal of Computer Applications》 2013-02
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Remote sensing image classification based on active learning with manifold structure

LIU Kang,QIAN Xu,WANG Ziqiang(School of Mechanical Electronic and Information Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China)  
To efficiently solve remote sensing image classification problem,a new classification algorithm based on manifold structure and Support Vector Machine(SVM) was proposed.Firstly,the proposed algorithm trained the SVM with initial training set and found the samples close to the decision hyperplane,then built the manifold structure of the samples by using Laplacian graph of the selected samples.The manifold structure was applied to find the representative samples for the classifier.The experimental evaluations were conducted on the hyperspectral images,and the effectiveness of the proposed algorithm was evaluated by comparing it with other active learning techniques exiting in the literature.The experimental results on data set confirm that the algorithm has higher classification accuracy.
【Fund】: 国家自然科学基金资助项目(70701013);; 中国博士后科学基金资助项目(2011M500035);; 高等学校博士学科点专项科研基金资助项目(20110023110002)
【CateGory Index】: TP18;TP751
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