46 search results - page 2 / 10 » Kernel quadratic discriminant analysis for small sample size... |
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
ICIP
2005
IEEE
14 years 6 months ago
2005
IEEE
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
MICCAI
2000
Springer
13 years 8 months ago
2000
Springer
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
CVPR
2005
IEEE
14 years 4 months ago
2005
IEEE
A novel framework called 2D Fisher Discriminant Analysis
(2D-FDA) is proposed to deal with the Small Sample
Size (SSS) problem in conventional One-Dimensional Linear
Discriminan...
CVPR
2001
IEEE
14 years 6 months ago
2001
IEEE
All positive examples are alike; each negative example is negative in its own way. During interactive multimedia information retrieval, the number of training samples fed-back by ...