Nonnegative Discriminant Matrix Factorization
IEEE Transactions on Circuits and Systems for Video Technology(2017)
摘要
Nonnegative matrix factorization (NMF), which aims at obtaining the nonnegative low-dimensional representation of data, has received wide attention. To obtain more effective nonnegative discriminant bases from the original NMF, in this paper, a novel method called nonnegative discriminant matrix factorization (NDMF) is proposed for image classification. NDMF integrates the nonnegative constraint, ...
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关键词
Matrix decomposition,Linear programming,Image reconstruction,Euclidean distance,Principal component analysis,Image classification,Convergence
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