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ICASSP
2009
IEEE
16 years 1 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
NIPS
1996
15 years 8 months ago
Analog VLSI Circuits for Attention-Based, Visual Tracking
A one-dimensional, visual tracking chip has been implemented using neuromorphic,analog VLSI techniques to modelselective visual attention in the control of saccadic and smooth pur...
Timothy K. Horiuchi, Tonia G. Morris, Christof Koc...
ICASSP
2009
IEEE
16 years 1 months ago
Fusion of fMRI, sMRI, and EEG data using canonical correlation analysis
Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separ...
Nicolle M. Correa, Yi-Ou Li, Tülay Adali, Vin...
ECCV
2006
Springer
16 years 8 months ago
Variational Shape and Reflectance Estimation Under Changing Light and Viewpoints
Abstract. Fitting parameterized 3D shape and general reflectance models to 2D image data is challenging due to the high dimensionality of the problem. The proposed method combines ...
Dana Cobzas, Martin Jägersand, Neil Birkbeck,...
ISBI
2006
IEEE
16 years 7 months ago
Automated tracking and modeling of microtubule dynamics
The method of microtubule tracking and dynamics analysis, presented here, improves upon the current means of manual and automated quantification of microtubule behavior. Key contr...
Motaz A. El Saban, Alphan Altinok, Austin J. Peck,...
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