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» Polynomial Conditional Random Fields for Signal Processing
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DAGM
2011
Springer
12 years 7 months ago
Putting MAP Back on the Map
Conditional Random Fields (CRFs) are popular models in computer vision for solving labeling problems such as image denoising. This paper tackles the rarely addressed but important ...
Patrick Pletscher, Sebastian Nowozin, Pushmeet Koh...
ICIP
2003
IEEE
14 years 9 months ago
A semantic representation for image retrieval
Robust semantic labeling of image regions is a basic problem in representing and retrieving image/video content. We propose an SVM-MRF framework to model features and their spatia...
Lei Wang, B. S. Manjunath
ICIP
2000
IEEE
14 years 9 months ago
A Wavelet-Based Image Denoising Technique Using Spatial Priors
We propose a new wavelet-based method for im age denoising that applies the Bayesian framework, using prior knowledge about the spatial clustering of the wavelet coefficients. Loc...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
CVPR
2008
IEEE
14 years 9 months ago
Visibility in bad weather from a single image
Bad weather, such as fog and haze, can significantly degrade the visibility of a scene. Optically, this is due to the substantial presence of particles in the atmosphere that abso...
Robby T. Tan
CORR
2010
Springer
93views Education» more  CORR 2010»
13 years 7 months ago
Rank Awareness in Joint Sparse Recovery
In this paper we revisit the sparse multiple measurement vector (MMV) problem, where the aim is to recover a set of jointly sparse multichannel vectors from incomplete measurement...
Mike E. Davies, Yonina C. Eldar