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...
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 ...
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...
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...
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...