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» Learning Flexible Features for Conditional Random Fields
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ICCV
2007
IEEE
15 years 11 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...
CVPR
2012
IEEE
13 years 3 days ago
Top-down visual saliency via joint CRF and dictionary learning
Top-down visual saliency facilities object localization by providing a discriminative representation of target objects and a probability map for reducing the search space. In this...
Jimei Yang, Ming-Hsuan Yang
ICIP
2003
IEEE
15 years 11 months ago
A semantic representation for image retrieval
Robust semantic labeling of image regions is a basic problem in representing and retrieving image/video content. We propose an SVM-MRF framework to model features and their spatia...
Lei Wang, B. S. Manjunath
ACL
2010
14 years 7 months ago
Understanding the Semantic Structure of Noun Phrase Queries
Determining the semantic intent of web queries not only involves identifying their semantic class, which is a primary focus of previous works, but also understanding their semanti...
Xiao Li
ICASSP
2009
IEEE
14 years 7 months ago
Applying discretized articulatory knowledge to dysarthric speech
This paper applies two dynamic Bayes networks that include theoretical and measured kinematic features of the vocal tract, respectively, to the task of labeling phoneme sequences ...
Frank Rudzicz