113 search results - page 14 / 23 » Hidden Markov Model} Induction by Bayesian Model Merging |
72
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CORR
2010
Springer
14 years 9 months ago
2010
Springer
We focus on credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. We replace the notion of strong independence commonly used in credal ne...
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ECAI
2004
Springer
15 years 3 months ago
2004
Springer
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
SSIAI
2000
IEEE
15 years 2 months ago
2000
IEEE
This paper deals with the problem of statistical unsupervised fusion of dependent sensors with its potential applications to multisensor image segmentation. On the one hand, Bayes...
JMLR
2010
14 years 4 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
CVPR
2000
IEEE
15 years 11 months ago
2000
IEEE
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...