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ICMCS
2007
IEEE
143views Multimedia» more  ICMCS 2007»
14 years 4 months ago
Hidden Conditional Random Fields for Meeting Segmentation
Automatic segmentation and classification of recorded meetings provides a basis towards understanding the content of a meeting. It enables effective browsing and querying in a me...
Stephan Reiter, Björn Schuller, Gerhard Rigol...
CVPR
2007
IEEE
14 years 12 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
CVBIA
2005
Springer
14 years 3 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
13 years 11 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
ICASSP
2011
IEEE
13 years 1 months ago
Discriminative duration modeling for speech recognition with segmental conditional random fields
This paper describes a new approach to modeling duration for LVCSR using SCARF, a toolkit for speech recognition with segmental conditional random fields. We utilize SCARF’s abi...
Justine T. Kao, Geoffrey Zweig, Patrick Nguyen