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CVPR
2009
IEEE
15 years 1 months ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
We present a new approach for the discriminative training of continuous-valued Markov Random Field (MRF) model parameters. In our approach we train the MRF model by optimizing t...
Kegan G. G. Samuel, Marshall F. Tappen
CVPR
2012
IEEE
11 years 8 months ago
A tiered move-making algorithm for general pairwise MRFs
A large number of problems in computer vision can be modeled as energy minimization problems in a markov random field (MRF) framework. Many methods have been developed over the y...
Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr
CVPR
2005
IEEE
14 years 8 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black
ICIP
2008
IEEE
14 years 8 months ago
Variational Bayesian image processing on stochastic factor graphs
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
Xin Li
MICCAI
2007
Springer
14 years 7 months ago
Characterizing Spatio-temporal Patterns for Disease Discrimination in Cardiac Echo Videos
Disease-specific understanding of echocardiographic sequences requires accurate characterization of spatio-temporal motion patterns. In this paper we present a method of automatic ...
Tanveer Fathima Syeda-Mahmood, Fei Wang, David Bey...