Data mining has emerged to address the problem of transforming data into useful knowledge. Although most data mining techniques, such as Association Rules, substantially reduce th...
The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algor...
Grigory Begelman, Michael Pechuk, Ehud Rivlin, Edm...
Compressive sampling (CS) is aimed at acquiring a signal or image from data which is deemed insufficient by Nyquist/Shannon sampling theorem. Its main idea is to recover a signal ...
With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applica...
—We develop sub-Nyquist sampling systems for analog signals comprised of several, possibly overlapping, finite duration pulses with unknown shapes and time positions. Efficient...