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CVPR
2008
IEEE
14 years 9 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
APGV
2004
ACM
176views Visualization» more  APGV 2004»
14 years 1 months ago
Towards perceptually realistic talking heads: models, methods and McGurk
Motivated by the need for an informative, unbiased and quantitative perceptual method for the development and evaluation of a talking head we are developing, we propose a new test...
Darren Cosker, Susan Paddock, A. David Marshall, P...
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
14 years 2 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
MICCAI
2005
Springer
14 years 8 months ago
Exploiting Temporal Information in Functional Magnetic Resonance Imaging Brain Data
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...
PR
2008
123views more  PR 2008»
13 years 7 months ago
Extensions of vector quantization for incremental clustering
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Edwin Lughofer