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ACL
2010
13 years 7 months ago
Jointly Optimizing a Two-Step Conditional Random Field Model for Machine Transliteration and Its Fast Decoding Algorithm
This paper presents a joint optimization method of a two-step conditional random field (CRF) model for machine transliteration and a fast decoding algorithm for the proposed metho...
Dong Yang, Paul R. Dixon, Sadaoki Furui
VMV
2001
209views Visualization» more  VMV 2001»
13 years 11 months ago
A Novel Probabilistic Model for 3D Object Recognition: Spin-Glass Markov Random Fields
This contribution presents a new class of MRF, that is inspired by methods of statistical physics. The new energy function assumes full-connectivity in the neighborhood system and...
Barbara Caputo, Sahla Bouattour, Dietrich Paulus
VLSM
2005
Springer
14 years 3 months ago
Entropy Controlled Gauss-Markov Random Measure Field Models for Early Vision
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...
Mariano Rivera, Omar Ocegueda, José L. Marr...
ICCV
2011
IEEE
12 years 9 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
CVPR
2010
IEEE
14 years 3 months ago
Semantic Context Modeling with Maximal Margin Conditional Random Fields for Automatic Image Annotation
Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources,...
Yu Xiang, Xiangdong Zhou, Zuotao Liu, Tat-seng chu...