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Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity

Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity

Sohil Shah
Tom Goldstein
Christoph Studer
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Papers citing "Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity"

2 / 2 papers shown
Title
On the Role and the Importance of Features for Background Modeling and Foreground Detection
On the Role and the Importance of Features for Background Modeling and Foreground Detection
T. Bouwmans
Caroline Silva
C. Marghes
M. S. Zitouni
H. Bhaskar
C. Frélicot
47
108
0
28 Nov 2016
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset
T. Bouwmans
A. Sobral
S. Javed
Soon Ki Jung
E. Zahzah
99
332
0
04 Nov 2015