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89
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CVPR
1999
IEEE
16 years 2 months ago
A Novel Bayesian Method for Fitting Parametric and Non-Parametric Models to Noisy Data
We o er a simple paradigm for tting models, parametric and non-parametric, to noisy data, which resolves some of the problems associated with classic MSE algorithms. This is done ...
Michael Werman, Daniel Keren
ICIP
2002
IEEE
16 years 2 months ago
A Bayesian approach to inferring vascular tree structure from 2D imagery
We describe a method for inferring tree-like vascular structures from 2D imagery. A Markov Chain Monte Carlo (MCMC) algorithm is employed to produce approximate samples from the p...
Abhir Bhalerao, Elke Thönnes, Roland Wilson, ...
72
Voted
FLAIRS
2000
15 years 2 months ago
Latin Hypercube Sampling in Bayesian Networks
Wepropose a schemefor producingLatin hypercube samples that can enhanceany of the existing sampling algorithms in Bayesiannetworks. Wetest this scheme in combinationwith the likel...
Jian Cheng, Marek J. Druzdzel
PAMI
2006
233views more  PAMI 2006»
15 years 16 days ago
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
This paper sets out a tracking framework, which is applied to the recovery of threedimensional hand motion from an image sequence. The method handles the issues of initialization,...
Björn Stenger, Arasanathan Thayananthan, Phil...
FPGA
2010
ACM
232views FPGA» more  FPGA 2010»
15 years 24 days ago
High-throughput bayesian computing machine with reconfigurable hardware
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Mingjie Lin, Ilia Lebedev, John Wawrzynek