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APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
13 years 9 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan
ICPR
2002
IEEE
14 years 19 days ago
Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models
In this paper, we propose a new recognition method of lung nodules from X-ray CT images using 3D Markov random field(MRF) models. Pathological shadow candidates are detected by a...
Hotaka Takizawa, Shinji Yamamoto, Tohru Matsumoto,...
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
14 years 6 days ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
BMCBI
2005
100views more  BMCBI 2005»
13 years 7 months ago
Evolutionary models for insertions and deletions in a probabilistic modeling framework
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
Elena Rivas
CVPR
2009
IEEE
15 years 2 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...