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- W2062856089 abstract "It has been proved that representation-based classification (RBC) can achieve high accuracy in face recognition. However, conventional RBC has a very high computational cost. Collaborative representation proposed in [1] not only has the advantages of RBC but also is computationally very efficient. In this paper, a combination of direct matching of images and collaborative representation is proposed for face recognition. Experimental results show that the proposed method can always classify more accurately than collaborative representation! The underlying reason is that direct matching of images and collaborative representation use different ways to calculate the dissimilarity between the test sample and training sample. As a result, the score obtained using direct matching of images is very complementary to the score obtained using collaborative representation. Actually, the analysis shows that the matching scores generated from direct matching of images and collaborative representation always have a low ..." @default.
- W2062856089 created "2016-06-24" @default.
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- W2062856089 date "2013-06-01" @default.
- W2062856089 modified "2023-09-24" @default.
- W2062856089 title "Combination of direct matching and collaborative representation for face recognition" @default.
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- W2062856089 doi "https://doi.org/10.1080/09500340.2013.814815" @default.
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