57 search results - page 10 / 12 » Adaptive Kernel Principal Component Analysis with Unsupervis... |
ICCV
2005
IEEE
14 years 7 months ago
2005
IEEE
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
ICCV
2005
IEEE
14 years 7 months ago
2005
IEEE
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
BMCBI
2010
13 years 5 months ago
2010
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
ICCV
2009
IEEE
14 years 10 months ago
2009
IEEE
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...
BMVC
2010
13 years 3 months ago
2010
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...