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» A variational method for Bayesian blind image deconvolution
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NIPS
1997
14 years 6 days ago
Bayesian Model of Surface Perception
Image intensity variations can result from several different object surface effects, including shading from 3-dimensional relief of the object, or paint on the surface itself. An ...
William T. Freeman, Paul A. Viola
ICCV
2003
IEEE
15 years 24 days ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
MICCAI
2009
Springer
14 years 3 months ago
Bayesian Maximal Paths for Coronary Artery Segmentation from 3D CT Angiograms
We propose a recursive Bayesian model for the delineation of coronary arteries from 3D CT angiograms (cardiac CTA) and discuss the use of discrete minimal path techniques as an eļ¬...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...
ICASSP
2011
IEEE
13 years 2 months ago
Nonstationary and temporally correlated source separation using Gaussian process
Blind source separation (BSS) is a process to reconstruct source signals from the mixed signals. The standard BSS methods assume a fixed set of stationary source signals with the ...
Hsin-Lung Hsieh, Jen-Tzung Chien
SCALESPACE
2007
Springer
14 years 5 months ago
On the Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional
In region-based image segmentation, two models dominate the ļ¬eld: the Mumford-Shah functional and statistical approaches based on Bayesian inference. Whereas the latter allow for...
Thomas Brox, Daniel Cremers