Robust auto-weighted projective low-rank and sparse recovery for visual representation.

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第一作者： Lei,Wang

第一单位： School of Computer Science and Technology, Soochow University, Suzhou 215006, China.

作者： Lei,Wang ^[1] ; Bangjun,Wang ^[1] ; Zhao,Zhang ^[2] ; Qiaolin,Ye ^[3] ; Liyong,Fu ^[4] ; Guangcan,Liu ^[5] ; Meng,Wang ^[6]

作者单位： School of Computer Science and Technology, Soochow University, Suzhou 215006, China. ^[1] School of Computer Science and Technology, Soochow University, Suzhou 215006, China; School of Computer Science & School of Artificial Intelligence, Hefei University of Technology, Hefei, China. Electronic address: cszzhang@gmail.com. ^[2] College of Information Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu, 210037, China. ^[3] Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China. Electronic address: fuliyong840909@163.com. ^[4] School of Information and Control, Nanjing University of Information Science and Technology, Nanjing, China. ^[5] School of Computer Science & School of Artificial Intelligence, Hefei University of Technology, Hefei, China. ^[6]

关键词 Auto-weighted low-rank and sparse recovery Classification Feature extraction Robust representation

主题词图像处理, 计算机辅助(Image Processing, Computer-Assisted);模式识别, 自动(Pattern Recognition, Automated)

DOI 10.1016/j.neunet.2019.05.007

PMID 31174048

发布时间 2019-11-08

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