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- W3130564212 abstract "As a new dimension reduction method, the two-dimensional principal component (2DPCA) can be well applied in face recognition, but it is susceptible to outliers. Therefore, this paper proposes a new 2DPCA algorithm based on angel-2DPCA. To reduce the reconstruction error and maximize the variance simultaneously, we choose F norm as the measure and propose the Fp-2DPCA algorithm. Considering that the image has two dimensions, we offer the Fp-2DPCA algorithm based on bilateral. Experiments show that, compared with other algorithms, the Fp-2DPCA algorithm has a better dimensionality reduction effect and better robustness to outliers." @default.
- W3130564212 created "2021-03-01" @default.
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- W3130564212 date "2021-01-01" @default.
- W3130564212 modified "2023-10-13" @default.
- W3130564212 title "Research on Face Recognition Algorithm Based on Robust 2DPCA" @default.
- W3130564212 doi "https://doi.org/10.4236/apm.2021.112010" @default.
- W3130564212 hasPublicationYear "2021" @default.
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