Robust bilateral Lp-norm two-dimensional linear discriminant analysis

Abstract Traditional linear discriminant analysis (LDA) may suffer from a sensitivity to outliers and the small sample size (SSS) problem, while the Lp-norm measure for 0

[1]  Dewen Hu,et al.  Comment on: "Two-dimensional locality preserving projections (2DLPP) with its application to palmprint recognition" , 2008, Pattern Recognit..

[2]  Songcan Chen,et al.  New Least Squares Support Vector Machines Based on Matrix Patterns , 2007, Neural Processing Letters.

[3]  Ping Zhong,et al.  Semi-supervised matrixized least squares support vector machine , 2017, Appl. Soft Comput..

[4]  Konstantinos N. Plataniotis,et al.  2DLDA as matrix-variate formulation of a separable 1DLDA , 2015, Pattern Recognit. Lett..

[5]  Jian Yang,et al.  Two-dimensional discriminant transform for face recognition , 2005, Pattern Recognit..

[6]  Palaiahnakote Shivakumara,et al.  (2D)2LDA: An efficient approach for face recognition , 2006, Pattern Recognit..

[7]  Daoqiang Zhang,et al.  (2D)2PCA: Two-directional two-dimensional PCA for efficient face representation and recognition , 2005, Neurocomputing.

[8]  Zilan Hu,et al.  Comment on: "Two-dimensional locality preserving projections (2DLPP) with its application to palmprint recognition" , 2008, Pattern Recognit..

[9]  Dongdong Li,et al.  Locality sensitive discriminant matrixized learning machine , 2017, Knowl. Based Syst..

[10]  Lei Wang,et al.  A framework of 2D Fisher discriminant analysis: application to face recognition with small number of training samples , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[11]  Jian Yang,et al.  From image vector to matrix: a straightforward image projection technique - IMPCA vs. PCA , 2002, Pattern Recognit..

[12]  Sheng Wang,et al.  Two-dimensional discriminant analysis based on Schatten p-norm for image feature extraction , 2017, J. Vis. Commun. Image Represent..

[13]  Ling Shao,et al.  Local Feature Discriminant Projection , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Jiashu Zhang,et al.  Linear Discriminant Analysis Based on L1-Norm Maximization , 2013, IEEE Transactions on Image Processing.

[15]  Xinbo Gao,et al.  Robust DLPP With Nongreedy $\ell _1$ -Norm Minimization and Maximization , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[16]  Chunxia Zhao,et al.  Recursive "concave-convex" Fisher Linear Discriminant with applications to face, handwritten digit and terrain recognition , 2012, Pattern Recognit..

[17]  Feiping Nie,et al.  A Non-Greedy Algorithm for L1-Norm LDA , 2017, IEEE Transactions on Image Processing.

[18]  Yuan-Hai Shao,et al.  Robust L1-norm two-dimensional linear discriminant analysis , 2015, Neural Networks.

[19]  M. Omair Ahmad,et al.  Two-dimensional FLD for face recognition , 2005, Pattern Recognit..

[20]  Hui Kong,et al.  Two-dimensional Fisher discriminant analysis: forget about small sample size problem [face recognition applications] , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[21]  Alejandro F. Frangi,et al.  Two-dimensional PCA: a new approach to appearance-based face representation and recognition , 2004 .

[22]  Zhongfei Zhang,et al.  Linear discriminant analysis using rotational invariant L1 norm , 2010, Neurocomputing.

[23]  Hau-San Wong,et al.  Face recognition based on 2D Fisherface approach , 2006, Pattern Recognit..

[24]  Shiguang Shan,et al.  Multi-View Discriminant Analysis , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Haixian Wang,et al.  L1-Norm Kernel Discriminant Analysis Via Bayes Error Bound Optimization for Robust Feature Extraction , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[26]  Jing Wang,et al.  Trace ratio 2DLDA with L1-norm optimization , 2017, Neurocomputing.

[27]  Xuelong Li,et al.  L1-Norm-Based 2DPCA , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[28]  Ming Li,et al.  2D-LDA: A statistical linear discriminant analysis for image matrix , 2005, Pattern Recognit. Lett..

[29]  Jieping Ye,et al.  Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection , 2008, IEEE Transactions on Neural Networks.

[30]  Lan Bai,et al.  MBLDA: A novel multiple between-class linear discriminant analysis , 2016, Inf. Sci..

[31]  George Saon,et al.  Minimum Bayes Error Feature Selection for Continuous Speech Recognition , 2000, NIPS.

[32]  Nojun Kwak,et al.  Principal Component Analysis Based on L1-Norm Maximization , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[33]  Lei Wang,et al.  Generalized 2D principal component analysis for face image representation and recognition , 2005, Neural Networks.

[34]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[35]  Jing Wang,et al.  Generalized 2-D Principal Component Analysis by Lp-Norm for Image Analysis , 2016, IEEE Transactions on Cybernetics.

[36]  I. Jolliffe.  Principal Component Analysis , 2002 .

[37]  E. K. Teoh,et al.  Generalized 2D principal component analysis , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[38]  Nojun Kwak,et al.  Principal Component Analysis by $L_{p}$ -Norm Maximization , 2014, IEEE Transactions on Cybernetics.

[39]  Nojun Kwak,et al.  Generalization of linear discriminant analysis using Lp-norm , 2013, Pattern Recognit. Lett..

[40]  Yuan-Hai Shao,et al.  Robust recursive absolute value inequalities discriminant analysis with sparseness , 2017, Neural Networks.

[41]  David Zhang,et al.  Local Linear Discriminant Analysis Framework Using Sample Neighbors , 2011, IEEE Transactions on Neural Networks.

[42]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[43]  Jing-Yu Yang,et al.  Algebraic feature extraction for image recognition based on an optimal discriminant criterion , 1993, Pattern Recognit..

[44]  Hong-Jie Xing,et al.  Linear discriminant analysis based on Zp-norm maximization , 2014, Proceedings of 2nd International Conference on Information Technology and Electronic Commerce.

[45]  Qin Tang,et al.  L1-Norm-Based Common Spatial Patterns , 2012, IEEE Transactions on Biomedical Engineering.

[46]  Yuan-Hai Shao,et al.  Robust L1-norm non-parallel proximal support vector machine , 2016 .