Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Modeling representations of image patches that are quasi-invariant to spatial deformations is an important problem in computer vision. In this paper, we propose a novel concept, t...
Jan Ernst, Maneesh Kumar Singh, Visvanathan Ramesh
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
ization method is an abstract function that transforms a scientific dataset into a visual representation to facilitate data exploration. In turn, a visualization display is the vis...
— Recent studies indicate the presence of a significant amount of idle licensed spectrum, in different time periods and geographic locations. Prompted by the latest regulatory ch...
George Alyfantis, Giannis F. Marias, Stathes Hadji...