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» Learning Regular Expressions from Noisy Sequences
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JMLR
2012
13 years 1 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
IVC
2008
101views more  IVC 2008»
14 years 11 months ago
Occlusion analysis: Learning and utilising depth maps in object tracking
Complex scenes such as underground stations and malls are composed of static occlusion structures such as walls, entrances, columns, turnstiles and barriers. Unless this occlusion...
Darrel Greenhill, John-Paul Renno, James Orwell, G...
CVPR
2004
IEEE
16 years 1 months ago
Probabilistic Expression Analysis on Manifolds
In this paper, we propose a probabilistic videobased facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observatio...
Ya Chang, Changbo Hu, Matthew Turk
102
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BMCBI
2007
165views more  BMCBI 2007»
14 years 11 months ago
Ab initio identification of human microRNAs based on structure motifs
Background: MicroRNAs (miRNAs) are short, non-coding RNA molecules that are directly involved in post-transcriptional regulation of gene expression. The mature miRNA sequence bind...
Markus Brameier, Carsten Wiuf
111
Voted
BMCBI
2010
176views more  BMCBI 2010»
14 years 11 months ago
Reverse engineering gene regulatory network from microarray data using linear time-variant model
nd: Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability...
Mitra Kabir, Nasimul Noman, Hitoshi Iba