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Nonnegative Discriminant Matrix Factorization
2017
IEEE transactions on circuits and systems for video technology (Print)
Nonnegative Matrix Factorization (NMF), which aims at obtaining the nonnegative low-dimensional representation of data, has been received widely attentions. To obtain more effective nonnegative discriminant bases from the original NMF, a novel method called Nonnegative Discriminant Matrix Factorization (NDMF) is proposed for image classification in this paper. NDMF integrates the nonnegative constraint, orthogonality and discriminant information in the objective function. NDMF considers the
doi:10.1109/tcsvt.2016.2539779
fatcat:cdvoyrgk4nh3nlf5ezz5zdtdke