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» Maximum entropy methods for biological sequence modeling
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ICIP
2004
IEEE
14 years 10 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte
ML
2010
ACM
141views Machine Learning» more  ML 2010»
13 years 7 months ago
Relational retrieval using a combination of path-constrained random walks
Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval o...
Ni Lao, William W. Cohen
NN
2006
Springer
13 years 9 months ago
Self-organizing neural networks to support the discovery of DNA-binding motifs
Identification of the short DNA sequence motifs that serve as binding targets for transcription factors is an important challenge in bioinformatics. Unsupervised techniques from t...
Shaun Mahony, Panayiotis V. Benos, Terry J. Smith,...
BMCBI
2008
214views more  BMCBI 2008»
13 years 7 months ago
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Jukka Corander, Pekka Marttinen, Jukka Siré...
ICASSP
2008
IEEE
14 years 3 months ago
Statistical approach to vocal tract transfer function estimation based on factor analyzed trajectory HMM
In this paper, we describe a novel statistical approach to the vocal tract transfer function (VTTF) estimation of a speech signal based on a factor analyzed trajectory hidden Mark...
Tomoki Toda, Keiichi Tokuda