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ECCV
1994
Springer
15 years 10 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
ECML
2006
Springer
15 years 10 months ago
Multiple-Instance Learning Via Random Walk
This paper presents a decoupled two stage solution to the multiple-instance learning (MIL) problem. With a constructed affinity matrix to reflect the instance relations, a modified...
Dong Wang, Jianmin Li, Bo Zhang
BILDMED
2008
147views Algorithms» more  BILDMED 2008»
15 years 7 months ago
Automatic Liver Segmentation Using the Random Walker Algorithm
In this paper we present a new method for fully automatic liver segmentation in computed tomography images. First, an initial set of seed points for the random walker algorithm is ...
Florian Maier, Andreas Wimmer, Grzegorz Soza, Jens...
COLING
2008
15 years 7 months ago
Word Sense Disambiguation for All Words using Tree-Structured Conditional Random Fields
We propose a supervised word sense disambiguation (WSD) method using tree-structured conditional random fields (TCRFs). By applying TCRFs to a sentence described as a dependency t...
Jun Hatori, Yusuke Miyao, Jun-ichi Tsujii
EMNLP
2008
15 years 7 months ago
Revealing the Structure of Medical Dictations with Conditional Random Fields
Automatic processing of medical dictations poses a significant challenge. We approach the problem by introducing a statistical framework capable of identifying types and boundarie...
Jeremy Jancsary, Johannes Matiasek, Harald Trost