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» Mixtures of Conditional Maximum Entropy Models
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CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge
MICCAI
2005
Springer
14 years 8 months ago
Tissue Classification of Noisy MR Brain Images Using Constrained GMM
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
Amit Ruf, Hayit Greenspan, Jacob Goldberger
ICPR
2010
IEEE
13 years 5 months ago
Exploiting Combined Multi-level Model for Document Sentiment Analysis
This paper focuses on the task of text sentiment analysis in hybrid online articles and web pages. Traditional approaches of text sentiment analysis typically work at a particular ...
Si Li, Hao Zhang, Weiran Xu, Guang Chen, Jun Guo
IJCV
2011
180views more  IJCV 2011»
13 years 2 months ago
Global Minimization for Continuous Multiphase Partitioning Problems Using a Dual Approach
This paper is devoted to the optimization problem of continuous multipartitioning, or multi-labeling, which is based on a convex relaxation of the continuous Potts model. In contr...
Egil Bae, Jing Yuan, Xue-Cheng Tai
NIPS
1998
13 years 8 months ago
An Entropic Estimator for Structure Discovery
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Matthew Brand