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CVPR
2005
IEEE
14 years 7 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
SCALESPACE
2007
Springer
13 years 11 months ago
Uniform and Textured Regions Separation in Natural Images Towards MPM Adaptive Denoising
Abstract. Natural images consist of texture, structure and smooth regions and this makes the task of filtering challenging mainly when it aims at edge and texture preservation. In...
Noura Azzabou, Nikos Paragios, Frederic Guichard
ICCV
2009
IEEE
14 years 10 months ago
Joint learning of visual attributes, object classes and visual saliency
We present a method to learn visual attributes (eg.“red”, “metal”, “spotted”) and object classes (eg. “car”, “dress”, “umbrella”) together. We assume imag...
Gang Wang, David Forsyth
ICPR
2006
IEEE
14 years 6 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
CVPR
2011
IEEE
13 years 1 months ago
Natural Image Denoising: Optimality and Inherent Bounds
The goal of natural image denoising is to estimate a clean version of a given noisy image, utilizing prior knowledge on the statistics of natural images. The problem has been stud...
Anat Levin, Boaz Nadler