Many problems in information extraction, text mining, natural language processing and other fields exhibit the same property: multiple prediction tasks are related in the sense th...
Using combinations of different volumetric datasets is becoming more common in scientific applications, especially medical environments such as neurosurgery where multiple imaging...
: In recent years the fusion of multimedia information from multiple real-time sources and databases has become increasingly important because of its practical significance in many...
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...