$Robust 2DPCA With <inline-formula> <tex-math notation="LaTeX">${F}$ </tex-math></inline-formula>-Norm Minimization$

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...

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Bibliographic Details
Main Authors:	Yong Wang, Qin Li
Format:	Article
Language:	English
Published:	IEEE 2019-01-01
Series:	IEEE Access
Subjects:	Two-dimensional principal component analysis robust feature extraction ℓ₂,₁-norm
Online Access:	https://ieeexplore.ieee.org/document/8721629/

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