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Discriminative Dictionary Pair Learning For Image Classification / Nguyen Hoang Vu, Tran Quoc Cuong, Tran Thanh Phong // Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics . - 2020. - tr. 53-69. - ISSN: 1813-9663
Ký hiệu phân loại (DDC): 006.6
Dictionary learning (DL) for sparse coding has been widely applied in the field of computer vision. Many DL approaches have been developed recently to solve pattern classification problems and have achieved promising performance. In this paper, to improve the discriminability of the popular dictionary pair learning (DPL) algorithm, we propose a new method called discriminative dictionary pair learning (DDPL) for image classification. To achieve the goal of signal representation and discrimination, we impose the incoherence constraints on the synthesis dictionary and the low- rank regularization on the analysis dictionary. The DDPL method ensures that the learned dictionary has a powerful discriminative ability and signals are more separable after coding. We evaluate the proposed method on benchmark image databases in comparison with existing DL methods. The experimental results demonstrate that our method outperforms many recently proposed dictionary learning approaches.
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