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PR
2008
144views more  PR 2008»
13 years 8 months ago
Kernel quadratic discriminant analysis for small sample size problem
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
ICDAR
2011
IEEE
12 years 8 months ago
A New Feature Optimization Method Based on Two-Directional 2DLDA for Handwritten Chinese Character Recognition
—LDA transformation is one of the popular feature dimension reduction techniques for the feature extraction in most handwritten Chinese characters recognition systems. The integr...
Xue Gao, Wenhuan Wen, Lianwen Jin
PAMI
2011
13 years 3 months ago
Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Hongping Cai, Krystian Mikolajczyk, Jiri Matas
CVPR
2004
IEEE
14 years 11 months ago
Random Sampling LDA for Face Recognition
Linear Discriminant Analysis (LDA) is a popular feature extraction technique for face recognition. However, It often suffers from the small sample size problem when dealing with t...
Xiaogang Wang, Xiaoou Tang
ICPR
2006
IEEE
14 years 2 months ago
Face Recognition Using Angular LDA and SVM Ensembles
One successful approach to feature extraction in face recognition problems is that of linear discriminant analysis (LDA). We examine an extension of this technique, called angular...
Raymond S. Smith, Josef Kittler, Miroslav Hamouz, ...