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FGR
2004
IEEE
135views Biometrics» more  FGR 2004»
13 years 8 months ago
Bayesian Fusion of Hidden Markov Models for Understanding Bimanual Movements
Understanding hand and body gestures is a part of a wide spectrum of current research in computer vision and Human-Computer Interaction. A part of this can be the recognition of m...
Atid Shamaie, Alistair Sutherland
MICCAI
2004
Springer
14 years 5 months ago
3D Bayesian Regularization of Diffusion Tensor MRI Using Multivariate Gaussian Markov Random Fields
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
Marcos Martín-Fernández, Carl-Fredri...
UAI
2000
13 years 6 months ago
Being Bayesian about Network Structure
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
Nir Friedman, Daphne Koller
ICIP
1995
IEEE
14 years 6 months ago
Variable resolution Markov modelling of signal data for image compression
Traditionally, Markov models have not been successfully used for compression of signal data other than binary image data. Due to the fact that exact substring matches in non-binar...
Mark Trumbo, Jacques Vaisey
CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 19 days ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh