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- W2994492036 abstract "Two-dimensional partial least squares (2DPLS) is an effective two-view data analysis technique. However, conventional 2DPLS only takes into account the column information of two-dimensional images. In this paper, we simultaneously consider the column-wise and row-wise information of two-dimensional face images. We first propose a row-based two-dimensional PLS (r2DPLS) approach and then further present a novel double-directional PLS (D(^{2})PLS) method. The proposed D(^{2})PLS method can be optimized by two eigenvalue subproblems. Experimental results on the AR, Yale, and AT&T face databases show that our D(^{2})PLS method can overall achieve better recognition accuracy than existing related methods." @default.
- W2994492036 created "2019-12-13" @default.
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- W2994492036 date "2019-01-01" @default.
- W2994492036 modified "2023-10-16" @default.
- W2994492036 title "D$$^{2}$$PLS: A Novel Bilinear Method for Facial Feature Fusion" @default.
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- W2994492036 doi "https://doi.org/10.1007/978-3-030-36808-1_44" @default.
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