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» Maximum Likelihood Estimators in Magnetic Resonance Imaging
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ICIP
2004
IEEE
14 years 11 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte
TIP
2002
98views more  TIP 2002»
13 years 9 months ago
Joint-MAP Bayesian tomographic reconstruction with a gamma-mixture prior
We address the problem of Bayesian image reconstruction with a prior that captures the notion of a clustered intensity histogram. The problem is formulated in the framework of a j...
Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi
BMEI
2009
IEEE
13 years 11 months ago
A Kurtosis and Skewness Based Criterion for Model Selection on Gaussian Mixture
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
Lin Wang, Jinwen Ma
ICIP
2010
IEEE
13 years 7 months ago
A non-stationary Hidden Markov Model of multiview video traffic
Multiview video is increasingly getting attention due to emerging applications such as 3DTV and immersive teleconferencing. In this paper, we present a non-stationary Hidden Marko...
Lorenzo Rossi, Jacob Chakareski, Pascal Frossard, ...
BMCBI
2007
141views more  BMCBI 2007»
13 years 9 months ago
A novel approach to detect hot-spots in large-scale multivariate data
Background: Progressive advances in the measurement of complex multifactorial components of biological processes involving both spatial and temporal domains have made it difficult...
Jianhua Wu, Keith M. Kendrick, Jianfeng Feng