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» A Bayesian Framework for Sensory Adaptation
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ICCV
2007
IEEE
13 years 9 months ago
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Bohyung Han, Seong-Wook Joo, Larry S. Davis
TSP
2008
101views more  TSP 2008»
13 years 7 months ago
Bayesian Compressive Sensing
The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be recons...
Shihao Ji, Ya Xue, Lawrence Carin
ALGORITHMICA
1998
103views more  ALGORITHMICA 1998»
13 years 7 months ago
On Bayes Methods for On-Line Boolean Prediction
We examine a general Bayesian framework for constructing on-line prediction algorithms in the experts setting. These algorithms predict the bits of an unknown Boolean sequence usin...
Nicolò Cesa-Bianchi, David P. Helmbold, San...
CVPR
2005
IEEE
14 years 9 months ago
Semi-Supervised Adapted HMMs for Unusual Event Detection
We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the applica...
Dong Zhang, Daniel Gatica-Perez, Samy Bengio, Iain...
DAGM
2006
Springer
13 years 11 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. ...