1018 search results - page 71 / 204 » Learning Probabilistic Models of Contours |
108
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CVPR
2011
IEEE
14 years 6 months ago
2011
IEEE
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
ICANN
2007
Springer
15 years 4 months ago
2007
Springer
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
103
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CVPR
2003
IEEE
15 years 12 months ago
2003
IEEE
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
TMI
1998
14 years 9 months ago
1998
Abstract—Segmenting lesions is a vital step in many computerized mass-detection schemes for digital (or digitized) mammograms. We have developed two novel lesion segmentation tec...
ACL
2008
2008
Using Adaptor Grammars to Identify Synergies in the Unsupervised Acquisition of Linguistic Structure
14 years 11 months ago
Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...