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70
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TSP
2008
173views more  TSP 2008»
14 years 9 months ago
Gaussian Mixture Modeling by Exploiting the Mahalanobis Distance
In this paper, the expectation-maximization (EM) algorithm for Gaussian mixture modeling is improved via three statistical tests. The first test is a multivariate normality criteri...
Dimitrios Ververidis, Constantine Kotropoulos
96
Voted
ICCV
2005
IEEE
15 years 3 months ago
Bayesian Body Localization Using Mixture of Nonlinear Shape Models
We present a 2D model-based approach to localizing human body in images viewed from arbitrary and unknown angles. The central component is a statistical shape representation of th...
Jiayong Zhang, Robert T. Collins, Yanxi Liu
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 1 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
TMI
2010
182views more  TMI 2010»
14 years 8 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
99
Voted
CVPR
2006
IEEE
15 years 11 months ago
Activity Analysis in Microtubule Videos by Mixture of Hidden Markov Models
We present an automated method for the tracking and dynamics modeling of microtubules -a major component of the cytoskeleton- which provides researchers with a previously unattain...
Alphan Altinok, Motaz A. El Saban, Austin J. Peck,...