28 search results - page 4 / 6 » Compressing Sparse Feature Vectors Using Random Ortho-Projec... |
CORR
2008
Springer
13 years 3 months ago
2008
Springer
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG comp...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
CIKM
2010
Springer
13 years 3 months ago
2010
Springer
In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...