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ICASSP
2010
IEEE
14 years 9 months ago
Under-determined convolutive blind source separation using spatial covariance models
This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency d...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...
86
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ESWA
2006
103views more  ESWA 2006»
14 years 9 months ago
Model gene network by semi-fixed Bayesian network
Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, le...
Tie-Fei Liu, Wing-Kin Sung, Ankush Mittal
ICASSP
2010
IEEE
14 years 8 months ago
Bayesian compressive sensing for phonetic classification
In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training...
Tara N. Sainath, Avishy Carmi, Dimitri Kanevsky, B...
ICIP
2006
IEEE
15 years 11 months ago
Joint Dimensionality Reduction, Classification and Segmentation of Hyperspectral Images
Dimensionality reduction, spectral classification and segmentation are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation appr...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
ICIP
2002
IEEE
15 years 11 months ago
A Bayesian approach to inferring vascular tree structure from 2D imagery
We describe a method for inferring tree-like vascular structures from 2D imagery. A Markov Chain Monte Carlo (MCMC) algorithm is employed to produce approximate samples from the p...
Abhir Bhalerao, Elke Thönnes, Roland Wilson, ...