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» Coarse-to-Fine Statistical Shape Model by Bayesian Inference
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FGCN
2008
IEEE
175views Communications» more  FGCN 2008»
15 years 4 months ago
Environment Recognition Based on Human Actions Using Probability Networks
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
Hiroshi Miki, Atsuhiro Kojima, Koichi Kise
JMLR
2010
143views more  JMLR 2010»
14 years 4 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
JMM2
2007
221views more  JMM2 2007»
14 years 9 months ago
Automatic Extraction of Femur Contours from Calibrated X-Ray Images using Statistical Information
— Automatic identification and extraction of bone contours from x-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D s...
Xiao Dong, Miguel Ángel González Bal...
ECCV
2008
Springer
15 years 11 months ago
Belief Propagation with Directional Statistics for Solving the Shape-from-Shading Problem
The Shape-from-Shading [SfS] problem infers shape from reflected light, collected using a camera at a single point in space only. Reflected light alone does not provide sufficient ...
Tom S. F. Haines, Richard C. Wilson
MICCAI
2006
Springer
15 years 10 months ago
A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data
Traditional techniques for statistical fMRI analysis are often based on thresholding of individual voxel values or averaging voxel values over a region of interest. In this paper w...
Hal S. Stern, Padhraic Smyth, Seyoung Kim