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» Variational Bayesian image modelling
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JMLR
2010
156views more  JMLR 2010»
15 years 1 months ago
Classification with Incomplete Data Using Dirichlet Process Priors
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
CVPR
2000
IEEE
16 years 8 months ago
Impact of Dynamic Model Learning on Classification of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...
Vladimir Pavlovic, James M. Rehg
PKDD
2005
Springer
122views Data Mining» more  PKDD 2005»
15 years 11 months ago
A Probabilistic Clustering-Projection Model for Discrete Data
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
MICCAI
2006
Springer
16 years 7 months ago
Probabilistic Brain Atlas Encoding Using Bayesian Inference
This paper addresses the problem of creating probabilistic brain atlases from manually labeled training data. We propose a general mesh-based atlas representation, and compare diff...
Koen Van Leemput
GI
2009
Springer
15 years 4 months ago
An Evolutionary Strategy for Model-based Segmentation of Medical Data
: Medical image segmentation often involves variants of deformable models to account for both the variability of object shapes and variation in image quality. Segmentation quality,...
Karin Engel, Klaus D. Toennies