Abstract-- Efficient detection of globally optimal surfaces representing object boundaries in volumetric datasets is important and remains challenging in many medical image analysi...
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
We present a new method for reconstructing digitally recorded off-axis Fresnel holograms. Currently-used reconstruction methods are based on the simulation and propagation of a re...
Michael Liebling, Thierry Blu, Etienne Cuche, Pier...
In our work, we address the problem of modeling social network generation which explains both link and group formation. Recent studies on social network evolution propose generati...
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...