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» Bayesian Parameter Estimation: A Monte Carlo Approach
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ISBI
2006
IEEE
14 years 11 months ago
Bayesian tracking for fluorescence microscopic imaging
Fluorescence microscopy is a powerful imaging tool for studying molecular dynamics in living cells. For quantitative motion analysis of subcellular structures robust and accurate ...
Ihor Smal, Wiro J. Niessen, Erik H. W. Meijering
CVPR
2005
IEEE
15 years 26 days ago
Learning to Estimate Human Pose with Data Driven Belief Propagation
We propose a statistical formulation for 2-D human pose estimation from single images. The human body configuration is modeled by a Markov network and the estimation problem is to...
Gang Hua, Ming-Hsuan Yang, Ying Wu
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 3 months ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel
INFORMATICALT
2011
112views more  INFORMATICALT 2011»
13 years 5 months ago
The Minimum Density Power Divergence Approach in Building Robust Regression Models
It is well known that in situations involving the study of large datasets where influential observations or outliers maybe present, regression models based on the Maximum Likeliho...
Alessandra Durio, Ennio Davide Isaia
LION
2009
Springer
129views Optimization» more  LION 2009»
14 years 5 months ago
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...