46 search results - page 4 / 10 » Kernel quadratic discriminant analysis for small sample size... |
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
Two Dimensional Linear Discriminant Analysis (2DLDA) has received much interest in recent years. However, 2DLDA could make pairwise distances between any two classes become signiï...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
A novel algorithm called Average Neighborhood Margin Maximization (ANMM) is proposed for supervised linear feature extraction. For each data point, ANMM aims at pulling the neighb...
ICDAR
2007
IEEE
14 years 1 months ago
2007
IEEE
The effectiveness of kernel fisher discrimination analysis (KFDA) has been demonstrated by many pattern recognition applications. However, due to the large size of Gram matrix to ...
PAMI
2012
11 years 10 months ago
2012
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...