The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte,...
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
—In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditio...
Adam Charles, Muhammad Salman Asif, Justin K. Romb...
In recent years, there has been a large increase in the amount of spatial data obtained from remote sensing, GPS receivers, communication terminals and other domains. Data warehous...
In this paper, we present an efficient method to synthesize large-scale scenes, such as broad city landscapes. To date, model based approaches have mainly been adopted for this pu...