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ICML
2009
IEEE
14 years 5 months ago
Multi-class image segmentation using conditional random fields and global classification
A key aspect of semantic image segmentation is to integrate local and global features for the prediction of local segment labels. We present an approach to multi-class segmentatio...
Nils Plath, Marc Toussaint, Shinichi Nakajima
ICIP
2010
IEEE
13 years 2 months ago
Fast semantic scene segmentation with conditional random field
In this paper, we present a fast approach to obtain semantic scene segmentation with high precision. We employ a two-stage classifier to label all image pixels. First, we use the ...
Wen Yang, Dengxin Dai, Bill Triggs, Gui-Song Xia, ...
IJCV
2008
186views more  IJCV 2008»
13 years 4 months ago
Multi-Class Segmentation with Relative Location Prior
Multi-class image segmentation has made significant advances in recent years through the combination of local and global features. One important type of global feature is that of i...
Stephen Gould, Jim Rodgers, David Cohen, Gal Elida...
MICCAI
2008
Springer
14 years 5 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...
SIAMIS
2010
378views more  SIAMIS 2010»
12 years 11 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert