Robust 2DPCA With <inline-formula> <tex-math notation="LaTeX">${F}$ </tex-math></inline-formula>-Norm Minimization
While feature extraction based on two-dimensional principal component analysis (2DPCA) is widely used in image recognition, such a method usually fails to handle the noise and outliers, because adopted F-norm square actually exaggerates the effect of outliers. To tackle the aforementioned problem, w...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8721629/ |