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CORR
2010
Springer
114views Education» more  CORR 2010»
13 years 10 months ago
Sequential Compressed Sensing
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
ECCV
2008
Springer
15 years 1 days ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
SIAMIS
2011
13 years 5 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
PERCOM
2009
ACM
14 years 5 months ago
iMAP: Indirect Measurement of Air Pollution with Cellphones
Abstract—In this paper, we introduce the cellphonebased indirect sensing problem. While participatory sensing aims at monitoring of a phenomenon by deploying a dense set of senso...
Murat Demirbas, Carole Rudra, Atri Rudra, Murat Al...
CVPR
2008
IEEE
15 years 5 days ago
Image super-resolution as sparse representation of raw image patches
This paper addresses the problem of generating a superresolution (SR) image from a single low-resolution input image. We approach this problem from the perspective of compressed s...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma