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CVPR
2008
IEEE
16 years 5 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
CVPR
2008
IEEE
16 years 5 months ago
Structure learning in random fields for heart motion abnormality detection
Coronary Heart Disease can be diagnosed by assessing the regional motion of the heart walls in ultrasound images of the left ventricle. Even for experts, ultrasound images are dif...
Glenn Fung, Kevin Murphy, Mark Schmidt, Róm...
ICPR
2008
IEEE
16 years 4 months ago
Change detection based on adaptive Markov Random Fields
Usually changes in remote sensing images go along with the appearance or disappearance of some edges. In addition, pixels located along the edges are likely to weakly influenced b...
Chunlei Huo, Hanqing Lu, Jian Cheng, Keming Chen, ...
ICML
2005
IEEE
16 years 4 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
CPAIOR
2009
Springer
15 years 9 months ago
Learning How to Propagate Using Random Probing
Abstract. In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usu...
Efstathios Stamatatos, Kostas Stergiou