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» Robust Bayesian Mixture Modelling
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NIPS
2008
15 years 7 months ago
Structure Learning in Human Sequential Decision-Making
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Daniel Acuña, Paul R. Schrater
PAMI
2002
108views more  PAMI 2002»
15 years 6 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery
163
Voted
IJCV
2007
134views more  IJCV 2007»
15 years 6 months ago
Multi-sensory and Multi-modal Fusion for Sentient Computing
This paper presents an approach to multi-sensory and multi-modal fusion in which computer vision information obtained from calibrated cameras is integrated with a large-scale sent...
Christopher Town
DAGM
2006
Springer
15 years 10 months ago
Dense Stereo by Triangular Meshing and Cross Validation
Dense depth maps can be estimated in a Bayesian sense from multiple calibrated still images of a rigid scene relative to a reference view [1]. This well-established probabilistic f...
Peter Wey, Bernd Fischer, Herbert Bay, Joachim M. ...
155
Voted
ECAI
2006
Springer
15 years 10 months ago
Learning Behaviors Models for Robot Execution Control
Robust execution of robotic tasks is a difficult problem. In many situations, these tasks involve complex behaviors combining different functionalities (e.g. perception, localizat...
Guillaume Infantes, Félix Ingrand, Malik Gh...