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166
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TMI
2010
182views more  TMI 2010»
15 years 2 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
168
Voted
AMDO
2010
Springer
15 years 1 months ago
Compatible Particles for Part-Based Tracking
Particle Filter methods are one of the dominant tracking paradigms due to its ability to handle non-gaussian processes, multimodality and temporal consistency. Traditionally, the e...
Brais Martínez, Marc Vivet, Xavier Binefa
136
Voted
ICCV
2009
IEEE
15 years 1 months ago
Face alignment through subspace constrained mean-shifts
Deformable model fitting has been actively pursued in the computer vision community for over a decade. As a result, numerous approaches have been proposed with varying degrees of ...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
152
Voted
AISS
2010
130views more  AISS 2010»
15 years 1 months ago
Neural Network Modeling for Proton Exchange Membrane Fuel Cell (PEMFC)
This paper presents the artificial intelligence techniques to control a proton exchange membrane fuel cell system process using particularly a methodology of dynamic neural networ...
Youssef M. ElSayed, Moataz H. Khalil, Khairia E. A...
187
Voted
AROBOTS
2011
14 years 10 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox