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	Two-dimensional principal component analysis based on Schatten p-norm for image feature extraction
	Du, Haishun[1]; Hu, Qingpu[2]; Jiang, Manman[3]; Zhang, Fan[4]
刊名	JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
	2015
卷号	32页码:55-62
关键词	Schatten p-norm Frebenius-norm Two-dimensional principal component analysis (2DPCA) Dimensionality reduction Feature extraction Subspace learning Image classification Convex optimization
ISSN号	1047-3203
DOI	http://dx.doi.org/10.1016/j.jvcir.2015.07.011
URL标识	查看原文
收录类别	SCI(E) ; EI
WOS记录号	WOS:000362388300004
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/5220421
专题	河南大学
作者单位	[1]Institute of Image Processing, Pattern Recognition, Henan University, Kaifeng, China[2]Institute of Image Processing, Pattern Recognition, Henan University, Kaifeng, China[3]Institute of Image Processing, Pattern Recognition, Henan University, Kaifeng, China[4]Institute of Image Processing, Pattern Recognition, Henan University, Kaifeng, China
推荐引用方式 GB/T 7714	Du, Haishun[1],Hu, Qingpu[2],Jiang, Manman[3],et al. Two-dimensional principal component analysis based on Schatten p-norm for image feature extraction[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2015,32:55-62.
APA	Du, Haishun[1],Hu, Qingpu[2],Jiang, Manman[3],&Zhang, Fan[4].(2015).Two-dimensional principal component analysis based on Schatten p-norm for image feature extraction.JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,32,55-62.
MLA	Du, Haishun[1],et al."Two-dimensional principal component analysis based on Schatten p-norm for image feature extraction".JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 32(2015):55-62.

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