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FLAIRS
2006
15 years 5 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
ENVSOFT
2002
187views more  ENVSOFT 2002»
15 years 3 months ago
AVTOP: a full integration of TOPMODEL into GIS
The integration of environmental models and Geographical Information Systems (GIS) usually takes two approaches: loose coupling and tight coupling. This paper, however, presents a...
Bo Huang, Bin Jiang
IPMI
2011
Springer
14 years 7 months ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
MICCAI
2008
Springer
16 years 5 months ago
Assessment of Reliability of Multi-site Neuroimaging Via Traveling Phantom Study
Abstract. This paper describes a framework for quantitative analysis of neuroimaging data of traveling human phantoms used for cross-site validation. We focus on the analysis of ma...
Sylvain Gouttard, Martin Styner, Marcel Prastawa...
CVPR
2008
IEEE
16 years 6 months ago
Increasing the density of Active Appearance Models
Active Appearance Models (AAMs) typically only use 50-100 mesh vertices because they are usually constructed from a set of training images with the vertices hand-labeled on them. ...
Krishnan Ramnath, Simon Baker, Iain Matthews, Deva...