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» A Conditional Random Field Model for Video Super-resolution
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141
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ICML
2001
IEEE
16 years 3 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
113
Voted
ICDAR
2007
IEEE
15 years 9 months ago
Document Image Segmentation Using a 2D Conditional Random Field Model
This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into acco...
Stéphane Nicolas, J. Dardenne, Thierry Paqu...
131
Voted
ICCPOL
2009
Springer
15 years 16 days ago
A Simple and Efficient Model Pruning Method for Conditional Random Fields
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Hai Zhao, Chunyu Kit
161
Voted
ACL
2004
15 years 4 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...
141
Voted
ICML
2004
IEEE
16 years 3 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...