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《Acta Electronica Sinica》 2017-08
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An Image Classification Method Using Graphically Regularized Coding Algorithm

YANG Sai;ZHAO Chun-xia;HU Bin;CHEN Feng;School of Electrical Engineering,Natong University;School of Computer Science and Engineering,Nanjing University of Science and Technology;School of Computer Science and Technology,Nantong University;  
In order to solve the problem that current coding schemes lost consistence between similar local features,this paper proposes a newgraphically regularized coding algorithm. This algorithm used any current coding scheme to get the initial coding coefficients,and utilized a regularized term to preserve locality constrains both in the feature space and the spatial domain of the image. Experimental results on popular benchmark datasets showthat our method improves the performances of the current coding algorithms,and the average classification accuracies of our proposed method in MSRcv2,Caltech101,Scene15,Indoor 67 and UIUC-sport has reached 91. 13%,76. 02%,83. 76%,44. 78% and 89. 05% respectively.
【Key Words】: bag-of-feature coding algorithm graphical model image classification
【Fund】: 江苏省普通高校自然科学研究面上项目(No.16KJB520037);; 国家自然科学基金(No.61602150);; 江苏省自然科学基金(No.BK20151273);; 南通市科技项目前沿与关键技术(No.MS22015100);; 江苏省博士后科研资助计划项目(No.1601013B)
【CateGory Index】: TP391.41
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