Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
We introduce a novel algorithm to address the challenges in magnetic resonance (MR) spectroscopic imaging. In contrast to classical sequential data processing schemes, the proposed...
Abstract. The convergence of Monte Carlo method for numerical integration can often be improved by replacing pseudorandom numbers (PRNs) with more uniformly distributed numbers kno...
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extr...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap...