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109
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CVPR
2005
IEEE
16 years 2 months ago
Diagram Structure Recognition by Bayesian Conditional Random Fields
Hand-drawn diagrams present a complex recognition problem. Elements of the diagram are often individually ambiguous, and require context to be interpreted. We present a recognitio...
Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka
EMNLP
2008
15 years 1 months ago
Revealing the Structure of Medical Dictations with Conditional Random Fields
Automatic processing of medical dictations poses a significant challenge. We approach the problem by introducing a statistical framework capable of identifying types and boundarie...
Jeremy Jancsary, Johannes Matiasek, Harald Trost
95
Voted
ICDAR
2005
IEEE
15 years 5 months ago
Learning Diagram Parts with Hidden Random Fields
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
Martin Szummer
JCB
2006
215views more  JCB 2006»
15 years 6 days ago
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation con...
Yan Liu 0002, Jaime G. Carbonell, Peter Weigele, V...
139
Voted
CVPR
2009
IEEE
16 years 7 months ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori