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SIAMIS
2010
378views more  SIAMIS 2010»
13 years 4 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
ACL
2004
13 years 11 months ago
Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
Brian Roark, Murat Saraclar, Michael Collins, Mark...
CVPR
2009
IEEE
15 years 4 months ago
Global Connectivity Potentials for Random Field Models
Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions a...
Sebastian Nowozin, Christoph H. Lampert
ICPR
2002
IEEE
14 years 10 months ago
Face Detection and Synthesis Using Markov Random Field Models
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Sarat C. Dass, Anil K. Jain, Xiaoguang Lu
ICIP
2005
IEEE
14 years 11 months ago
A segmentation method using compound Markov random fields based on a general boundary model
Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
Jue Wu, Albert C. S. Chung