This paper presents a novel spatio-temporal Markov random field (MRF) for video denoising. Two main issues are addressed in this paper, namely, the estimation of noise model and t...
Wireless sensor networks (WSNs) pose challenges not present in classical distributed systems: resource limitations, high failure rates, and ad hoc deployment. The lossy nature of w...
Random walk graph and Markov chain based models are used heavily in many data and system analysis domains, including web, bioinformatics, and queuing. These models enable the desc...
In this abstract, we provide an overview of our survey of randomized techniques for exploiting the parallelism in string matching problems. Broadly, the study of string matching fa...
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...