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TMI
2010
182views more  TMI 2010»
13 years 3 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
CVPR
2008
IEEE
14 years 7 months ago
Edge preserving spatially varying mixtures for image segmentation
A new hierarchical Bayesian model is proposed for image segmentation based on Gaussian mixture models (GMM) with a prior enforcing spatial smoothness. According to this prior, the...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
JMLR
2011
167views more  JMLR 2011»
12 years 12 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
AMFG
2007
IEEE
255views Biometrics» more  AMFG 2007»
13 years 9 months ago
A New Probabilistic Model for Recognizing Signs with Systematic Modulations
Abstract. This paper addresses an aspect of sign language (SL) recognition that has largely been overlooked in previous work and yet is integral to signed communication. It is the ...
Sylvie C. W. Ong, Surendra Ranganath
IJON
2010
189views more  IJON 2010»
13 years 3 months ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin