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- W1747367457 abstract "Abstract This study develops a novel efficient coupled distance metric learning algorithm called coupled marginal discriminant mappings (CMDM). It can provide a low-resolution face recognition method with coupled mappings, making the data points in the original high and low resolution features projected into a unified space, where classification is implemented. At the same time, it makes samples from the same class gather more closely while makes samples of distinct class disperse more separately with a large margin. Thus, for the low-resolution face recognition issue, the proposed method can be leveraged to avoid dimensional mismatch problem and fill different-resolution data gap. The experimental evaluation based on the AR and FERET face databases demonstrates that CMDM can achieve highly competitive performance comparing favorably with the existing state-of-the-art low-resolution face recognition methods." @default.
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- W1747367457 date "2015-12-01" @default.
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- W1747367457 title "Coupled marginal discriminant mappings for low-resolution face recognition" @default.
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- W1747367457 doi "https://doi.org/10.1016/j.ijleo.2015.08.138" @default.
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