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Link to original content: https://unpaywall.org/10.1587/TRANSFUN.E100.A.3081
2017 Volume E100.A Issue 12 Pages 3081-3085
In this work, two new proposed NMF models are developed for facial expression recognition. They are called maximum volume constrained nonnegative matrix factorization (MV_NMF) and maximum volume constrained graph nonnegative matrix factorization (MV_GNMF). They achieve sparseness from a larger simplicial cone constraint and the extracted features preserve the topological structure of the original images.
