We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
Image-based rendering data sets, such as light fields, require efficient compression due to their large data size, but also easy random access when rendering from the data set. Ef...
Abstract. A central task when integrating data from different sources is to detect identical items. For example, price comparison websites have to identify offers for identical p...
Abstract— We consider the scenario of distributed data aggregation in wireless sensor networks, where each sensor can obtain and estimate the information of the whole sensing fi...