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 ...
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...
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...
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...
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 ...