1875 search results - page 30 / 375 » Kernel Methods for Pattern Analysis |
NIPS
2008
13 years 11 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
ICCV
2009
IEEE
13 years 8 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
ICIP
2007
IEEE
14 years 4 months ago
2007
IEEE
In this paper a novel non-linear subspace method for face verification is proposed. The problem of face verification is considered as a two-class problem (genuine versus imposto...
ICCV
2003
IEEE
15 years 8 days ago
2003
IEEE
This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
TOG
2008
13 years 10 months ago
2008
Achieving intuitive control of animated surface deformation while observing a specific style is an important but challenging task in computer graphics. Solutions to this task can ...