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» Bayesian Parameter Estimation: A Monte Carlo Approach
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JCNS
2010
104views more  JCNS 2010»
14 years 10 months ago
A new look at state-space models for neural data
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
SSPR
2004
Springer
15 years 5 months ago
An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data
We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
Despina Kontos, Vasileios Megalooikonomou, Marc J....
CVIU
2006
158views more  CVIU 2006»
14 years 12 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu
CSDA
2011
14 years 6 months ago
Mapping electron density in the ionosphere: A principal component MCMC algorithm
The outer layers of the Earth’s atmosphere are known as the ionosphere, a plasma of free electrons and positively charged atomic ions. The electron density of the ionosphere var...
Eman Khorsheed, Merrilee Hurn, Christopher Jenniso...
FGR
2011
IEEE
263views Biometrics» more  FGR 2011»
14 years 3 months ago
Exploiting long-term observations for track creation and deletion in online multi-face tracking
— In many visual multi-object tracking applications, the question when to add or remove a target is not trivial due to, for example, erroneous outputs of object detectors or obse...
Stefan Duffner, Jean-Marc Odobez