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» Markov Random Field Modeling in Computer Vision
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RECOMB
2005
Springer
14 years 9 months ago
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition
Abstract. Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmenta...
Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanath...
ICASSP
2007
IEEE
14 years 3 months ago
Markov Random Field Energy Minimization via Iterated Cross Entropy with Partition Strategy
This paper introduces a novel energy minimization method, namely iterated cross entropy with partition strategy (ICEPS), into the Markov random field theory. The solver, which is...
Jue Wu, Albert C. S. Chung
ICPR
2008
IEEE
14 years 10 months ago
A new objective function for sequence labeling
We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
Hisashi Kashima, Yuta Tsuboi
CVPR
2003
IEEE
14 years 11 months ago
Object Segmentation in Videos from Moving Camera with MRFs on Color and Motion Features
In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based ...
Rita Cucchiara, Andrea Prati, Roberto Vezzani
DAS
2010
Springer
13 years 11 months ago
Overlapped text segmentation using Markov random field and aggregation
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
Xujun Peng, Srirangaraj Setlur, Venu Govindaraju, ...