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CORR
2008
Springer
178views Education» more  CORR 2008»
14 years 10 months ago
Model-Based Compressive Sensing
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K N elements from a...
Richard G. Baraniuk, Volkan Cevher, Marco F. Duart...
CGF
2011
14 years 1 months ago
A Sparse Parametric Mixture Model for BTF Compression, Editing and Rendering
Bidirectional texture functions (BTFs) represent the appearance of complex materials. Three major shortcomings with BTFs are the bulky storage, the difficulty in editing and the ...
Hongzhi Wu, Julie Dorsey, Holly E. Rushmeier
DCC
2003
IEEE
15 years 9 months ago
PPM Model Cleaning
The Prediction by Partial Matching (PPM) algorithm uses a cumulative frequency count of input symbols in different contexts to estimate their probability distribution. Excellent c...
Milenko Drinic, Darko Kirovski, Miodrag Potkonjak
ICASSP
2010
IEEE
14 years 10 months ago
Adaptive compressed sensing - A new class of self-organizing coding models for neuroscience
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
ACSAC
2003
IEEE
15 years 3 months ago
Automatic Reassembly of Document Fragments via Context Based Statistical Models
Reassembly of fragmented objects from a collection of randomly mixed fragments is a common problem in classical forensics. In this paper we address the digital forensic equivalent...
Kulesh Shanmugasundaram, Nasir D. Memon