68 search results - page 8 / 14 » Testing for Homogeneity with Kernel Fisher Discriminant Anal... |
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 ...
TNN
2008
13 years 7 months ago
2008
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
ICPR
2008
IEEE
14 years 8 months ago
2008
IEEE
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
CVPR
2005
IEEE
14 years 1 months ago
2005
IEEE
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
This paper describes a complete approach to detect, localize and describe network patterns. Such texture is automatically detected with Gaussian derivative kernels and Fisher line...