We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...
This paper presents a loosely coupled service-composition paradigm. This paradigm employs a distributed data flow that differs markedly from centralized information flow adopted b...
David Liu, Jun Peng, Kincho H. Law, Gio Wiederhold
— In this paper, we present a solution to the general problem of flow control for both unicast and multicast IP networks. We formulate a convex optimization problem that can be ...
Network traffic modeling generally views traffic as a superposition of flows that creates a timeseries of volume counts (e.g. of bytes or packets). What is omitted from this view ...
The present work investigates the structural and dynamical properties of aNobii1 , a social bookmarking system designed for readers and book lovers. Users of aNobii provide informa...
Luca Maria Aiello, Alain Barrat, Ciro Cattuto, Gia...