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» Piecewise pseudolikelihood for efficient training of conditi...
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89
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ECCV
2006
Springer
16 years 1 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
93
Voted
ACL
2010
14 years 9 months ago
Practical Very Large Scale CRFs
Conditional Random Fields (CRFs) are a widely-used approach for supervised sequence labelling, notably due to their ability to handle large description spaces and to integrate str...
Thomas Lavergne, Olivier Cappé, Franç...
CVPR
2007
IEEE
16 years 1 months ago
Latent-Dynamic Discriminative Models for Continuous Gesture Recognition
Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper, we develop a discriminative framework for simultaneous se...
Louis-Philippe Morency, Ariadna Quattoni, Trevor D...
BMCBI
2006
154views more  BMCBI 2006»
14 years 11 months ago
Automated recognition of malignancy mentions in biomedical literature
Background: The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of ...
Yang Jin, Ryan T. McDonald, Kevin Lerman, Mark A. ...
99
Voted
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 2 days ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...