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CVPR
2010
IEEE
15 years 7 months ago
Heterogeneous Conditional Random Field: Realizing Joint Detection and Segmentation of Cell Regions in Microscopic Images
Detecting and segmenting cell regions in microscopic images is a challenging task, because cells typically do not have rich features, and their shapes and appearances are highly i...
Jiyan Pan, Takeo Kanade
122
Voted
ICASSP
2007
IEEE
15 years 6 months ago
Context-Based Concept Fusion with Boosted Conditional Random Fields
The contextual relationships among different semantic concepts provide important information for automatic concept detection in images/videos. We propose a new context-based conce...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
101
Voted
SIBGRAPI
2006
IEEE
15 years 6 months ago
Improving 2D mesh image segmentation with Markovian Random Fields
Traditional mesh segmentation methods normally operate on geometrical models with no image information. On the other hand, 2D image-based mesh generation and segmentation counterp...
Alex Jesus Cuadros-Vargas, Leandro C. Gerhardinger...
102
Voted
ACL
2008
15 years 1 months ago
Efficient, Feature-based, Conditional Random Field Parsing
Discriminative feature-based methods are widely used in natural language processing, but sentence parsing is still dominated by generative methods. While prior feature-based dynam...
Jenny Rose Finkel, Alex Kleeman, Christopher D. Ma...
JMLR
2010
145views more  JMLR 2010»
14 years 7 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever