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» Source Separation with Gaussian Process Models
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ISBI
2008
IEEE
14 years 8 months ago
Convex analysis and separation of composite signals in DCE-MRI
Dynamic functional imaging promises powerful tools for the visualization and elucidation of important diseasecausing biological processes, where the pixels often represent a compo...
Li Chen, Tsung-Han Chan, Peter L. Choyke, Chong-Yu...
ICASSP
2010
IEEE
13 years 7 months ago
Near-field adaptive beamforming and source localization in the spacetime frequency domain
We revisit the topics of near-field adaptive beamforming and source localization following an alternative approach based on a spatiotemporal spectral representation of the acoust...
Francisco Pinto, Martin Vetterli
ICASSP
2011
IEEE
12 years 11 months ago
Collaborative sources identification in mixed signals via hierarchical sparse modeling
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Pablo Sprechmann, Ignacio Ramírez, Pablo Ca...
NIPS
2003
13 years 8 months ago
Probabilistic Inference in Human Sensorimotor Processing
When we learn a new motor skill, we have to contend with both the variability inherent in our sensors and the task. The sensory uncertainty can be reduced by using information abo...
Konrad P. Körding, Daniel M. Wolpert
ICIP
2010
IEEE
13 years 4 months ago
Robust and efficient background subtraction by quadratic polynomial fitting
We present a background subtraction algorithm aimed at efciency and robustness to common sources of disturbance such as illumination changes, camera gain and exposure variations, ...
Alessandro Lanza, Federico Tombari, Luigi di Stefa...