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» Robust Principal Component Analysis for Computer Vision
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CVPR
2007
IEEE
14 years 9 months ago
Robust Estimation of Texture Flow via Dense Feature Sampling
Texture flow estimation is a valuable step in a variety of vision related tasks, including texture analysis, image segmentation, shape-from-texture and texture remapping. This pap...
Yu-Wing Tai, Michael S. Brown, Chi-Keung Tang
ICIP
2008
IEEE
14 years 9 months ago
Principal components for non-local means image denoising
This paper presents an image denoising algorithm that uses principal component analysis (PCA) in conjunction with the non-local means image denoising. Image neighborhood vectors u...
Tolga Tasdizen
ICCV
2007
IEEE
14 years 1 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
IDA
1998
Springer
13 years 7 months ago
Fast Dimensionality Reduction and Simple PCA
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
Matthew Partridge, Rafael A. Calvo
BMCBI
2010
144views more  BMCBI 2010»
13 years 7 months ago
Super-sparse principal component analyses for high-throughput genomic data
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
Donghwan Lee, Woojoo Lee, Youngjo Lee, Yudi Pawita...