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ICA
2010
Springer
13 years 10 months ago
Adaptive Underdetermined ICA for Handling an Unknown Number of Sources
Independent Component Analysis is the best known method for solving blind source separation problems. In general, the number of sources must be known in advance. In many cases, pre...
Andreas Sandmair, Alam Zaib, Fernando Puente Le&oa...
IJON
2008
116views more  IJON 2008»
13 years 9 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter
JMLR
2006
105views more  JMLR 2006»
13 years 9 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen
PAMI
2006
138views more  PAMI 2006»
13 years 9 months ago
Context-Based Segmentation of Image Sequences
We describe an algorithm for context-based segmentation of visual data. New frames in an image sequence (video) are segmented based on the prior segmentation of earlier frames in ...
Jacob Goldberger, Hayit Greenspan
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
15 years 4 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge