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» Fast Independent Component Analysis in Kernel Feature Spaces
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IJON
2006
169views more  IJON 2006»
13 years 7 months ago
Denoising using local projective subspace methods
In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on app...
Peter Gruber, Kurt Stadlthanner, Matthias Böh...
ICPR
2006
IEEE
14 years 8 months ago
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models
Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
Datong Chen, Jie Yang
ICASSP
2008
IEEE
14 years 1 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner
EOR
2007
165views more  EOR 2007»
13 years 7 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
ICPR
2000
IEEE
13 years 12 months ago
Eigensnakes for Vessel Segmentation in Angiography
In this paper we introduce a new deformable model, called eigensnake, for segmentation of elongated structures in a probabilistic framework. Instead of snake attraction by speciï¬...
Ricardo Toledo, Xavier Orriols, Petia Radeva, Xavi...