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» A Markov Random Field Model of Microarray Gridding
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UAI
2004
14 years 11 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
UAI
2004
14 years 11 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
PAMI
2008
161views more  PAMI 2008»
14 years 9 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...
ESTIMEDIA
2008
Springer
14 years 11 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...
ICPR
2002
IEEE
15 years 10 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