2D pattern recognition method is very useful for beginners, including 2DPCA and 2DLDA latest methods.

论文2dPCAand 2dlda\(2D)2LDA An efficient approach for face recognition2006.pdf
..................\(2D)2PCA 20062-Directional 2-Dimensional PCA for Efficient Face Representation and Recognition2005.pdf
..................\(2dpca add 2dlda)2006TWO-DIMENSIONAL LINEAR DISCRIMINANT ANALYSIS OF PRINCIPLE COMPONENT.pdf
..................\(B2DPCA2006)Class-Specific Subspace-Based Two-Dimensional Principal Component Analysis2006.pdf
..................\1991face recognition using eigenfaces.pdf
..................\6006Face recognition from a single image per person Asurvey.pdf
..................\A tutorial on Principal Components Analysis.pdf
..................\Afast kernel-based nonlinear discriminant analysis.pdf
..................\Face Recognition Based on Face-Specific Subspace2005.pdf
..................\Face Recognition based on variant 2DPCA-based approaches in robot environments2007.pdf
..................\FACE RECOGNITION FOR SMART INTERACTIONS.pdf
..................\FACE RECOGNITION USING 2DLDA ALGORITHM2005.pdf
..................\Face recognition using assembled matrix distance metric based 2DLDA 2006.pdf
..................\IMAGE PCA A NEW APPROACH FOR FACE RECOGNITION2007.pdf
..................\Multilinear Discriminant Analysis2007.pdf
..................\On solving the face recognition problem with one training sample per subject.pdf
..................\Orthogonal Neighborhood Preserving projections a prijecrion-based dimensionality reduction technique2007PAMI.pdf
..................\The Bas-Relief Ambiguity.pdf
..................\TWO-DIMENSIONAL ADAPTIVE DISCRIMINANT ANALYSIS2007.pdf
..................\Two-dimensional discriminant transform for face recognition2005.pdf
..................\Two-dimensional FLD for face recognition2005.pdf
..................\基于对角DCT与2DPCA算法的人脸识别.pdf
论文2dPCAand 2dlda

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