93 search results - page 9 / 19 » Subspace independent component analysis using vector kurtosi... |
ECCV
2000
Springer
14 years 9 months ago
2000
Springer
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
ICANN
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
ICA
2007
Springer
13 years 11 months ago
2007
Springer
Independent Component Analysis (ICA) is a statistical method for expressing an observed set of random vectors as a linear combination of statistically independent components. This...
ICANN
2003
Springer
14 years 29 days ago
2003
Springer
In independent component analysis problems, when we use a one-unit objective function to iteratively estimate several independent components, the uncorrelatedness between the indep...
WACV
2008
IEEE
14 years 2 months ago
2008
IEEE
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...