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ECCV
1994
Springer
15 years 1 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
ICIP
2006
IEEE
15 years 3 months ago
Discontinuity-Adaptive De-Interlacing Scheme Using Markov Random Field Model
— In this paper, a de-interlacing algorithm to find the optimal deinterlaced results given accuracy-limited motion information is proposed. The de-interlacing process is formula...
Min Li, Truong Q. Nguyen
ICPR
2000
IEEE
15 years 10 months ago
A Markov Random Field Model for Automatic Speech Recognition
Speech can be represented as a time/frequency distribution of energy using a multi-band filter bank. A Markov random field model, which takes into account the possible time asynch...
Gérard Chollet, Guillaume Gravier, Marc Sig...
SIGIR
2005
ACM
15 years 3 months ago
A Markov random field model for term dependencies
This paper develops a general, formal framework for modeling term dependencies via Markov random fields. The model allows for arbitrary text features to be incorporated as eviden...
Donald Metzler, W. Bruce Croft
CVPR
2009
IEEE
16 years 4 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...