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TMI
2008
138views more  TMI 2008»
13 years 8 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
ICIP
2001
IEEE
14 years 10 months ago
Supervised segmentation and tracking of nonrigid objects using a "mixture of histograms" model
Segmentation and tracking of objects in video sequences is important for a number of applications. In the supervised variant, segmentation can be achieved by modelling the probabi...
Mark Everingham, Barry T. Thomas
ICIP
1995
IEEE
14 years 10 months ago
3D super-resolution using generalized sampling expansion
A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorith...
Hassan Shekarforoush, Marc Berthod, Josiane Zerubi...
CVPR
2008
IEEE
14 years 11 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
ICASSP
2009
IEEE
13 years 6 months ago
Robust Bayesian tracking on Riemannian manifolds via fragments-based representation
Recently, the covariance region descriptor [1] has been proved robust and versatile for a modest computational cost. It enables efficient fusion of different types of features. Ba...
Yi Wu, Jinqiao Wang, Hanqing Lu