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» A Markov Random Field Model of Microarray Gridding
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101
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UAI
2004
15 years 4 months ago
Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
Mathias Drton, Thomas S. Richardson
143
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UAI
2004
15 years 4 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
159
Voted
PAMI
2008
161views more  PAMI 2008»
15 years 3 months ago
Multilayered 3D LiDAR Image Construction Using Spatial Models in a Bayesian Framework
Standard 3D imaging systems process only a single return at each pixel from an assumed single opaque surface. However, there are situations when the laser return consists of multip...
Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J...
126
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ESTIMEDIA
2008
Springer
15 years 5 months ago
Parallelization of belief propagation method on embedded multicore processors for stereo vision
Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation...
Chi-Hua Lai, Kun-Yuan Hsieh, Shang-Hon Lai, Jenq K...
157
Voted
ICPR
2002
IEEE
16 years 4 months ago
Multicue MRF Image Segmentation: Combining Texture and Color Features
Herein, we propose a new Markov random field (MRF) image segmentation model which aims at combining color and texture features. The model has a multi-layer structure: Each feature...
Zoltan Kato, Ting-Chuen Pong, Song Guo Qiang