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ISMB
1993
15 years 3 months ago
Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein familyor the columns of a multiple alignment of that famil...
Michael Brown, Richard Hughey, Anders Krogh, I. Sa...
GECCO
2009
Springer
101views Optimization» more  GECCO 2009»
15 years 8 months ago
Modeling UCS as a mixture of experts
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
ICIP
2001
IEEE
16 years 3 months ago
Supervised segmentation and tracking of nonrigid objects using a "mixture of histograms" model
Segmentation and tracking of objects in video sequences is important for a number of applications. In the supervised variant, segmentation can be achieved by modelling the probabi...
Mark Everingham, Barry T. Thomas
ICIP
2001
IEEE
16 years 3 months ago
Multiresolution Gaussian mixture models for visual motion estimation
This paper introduces a new generalisation of scale-space and pyramids, which combines statistical modelling with a spatial representation. The representation uses the familiar co...
Roland Wilson, Andrew Calway
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
16 years 4 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson