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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
TSMC
2010
13 years 2 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
JMLR
2008
151views more  JMLR 2008»
13 years 7 months ago
Learning to Combine Motor Primitives Via Greedy Additive Regression
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
Manu Chhabra, Robert A. Jacobs
ICIP
2007
IEEE
14 years 9 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
TIP
2008
153views more  TIP 2008»
13 years 7 months ago
Hierarchical Color Correction for Camera Cell Phone Images
In this paper, we propose a hierarchical color correction algorithm for enhancing the color of digital images obtained from low quality digital image capture devices such as cell ...
Hasib Siddiqui, Charles A. Bouman