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ICPR
2008
IEEE
14 years 9 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
ICASSP
2007
IEEE
14 years 2 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
CVBIA
2005
Springer
14 years 1 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
IVC
2008
141views more  IVC 2008»
13 years 7 months ago
Segmentation of color images via reversible jump MCMC sampling
Reversible jump Markov chain Monte Carlo (RJMCMC) is a recent method which makes it possible to construct reversible Markov chain samplers that jump between parameter subspaces of...
Zoltan Kato
MICCAI
2008
Springer
14 years 9 months ago
Segmenting Brain Tumors Using Pseudo-Conditional Random Fields
Locating Brain tumor segmentation within MR (magnetic resonance) images is integral to the treatment of brain cancer. This segmentation task requires classifying each voxel as eith...
Chi-Hoon Lee, Shaojun Wang, Albert Murtha, Matt...