46 search results - page 6 / 10 » Kernel quadratic discriminant analysis for small sample size... |
CVPR
2005
IEEE
14 years 9 months ago
2005
IEEE
In this paper, we present a novel approach to solving the supervised dimensionality reduction problem by encoding an image object as a general tensor of 2nd or higher order. First...
CORR
2008
Springer
13 years 7 months ago
2008
Springer
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
ECCV
2006
Springer
14 years 9 months ago
2006
Springer
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
IJPRAI
2006
13 years 7 months ago
2006
Linear Discriminant Analysis (LDA) is a popular feature extraction technique in statistical pattern recognition. However, it often suffers from the small sample size problem when ...