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NIPS
2004
15 years 1 months ago
Semi-Markov Conditional Random Fields for Information Extraction
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...
Sunita Sarawagi, William W. Cohen
ICASSP
2011
IEEE
14 years 4 months ago
Automatic speech recognition using Hidden Conditional Neural Fields
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagaw...
113
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MICCAI
2008
Springer
16 years 1 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...
CVBIA
2005
Springer
15 years 6 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...
EMNLP
2006
15 years 1 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew