This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
In this paper we present an approach to multi-objective exploration of the mapping space of a mesh-based network-on-chip architecture. Based on evolutionary computing techniques, ...
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...
Abstract-- Associative classification is a new classification approach integrating association mining and classification. It becomes a significant tool for knowledge discovery and ...
Risk assessment in regions with low earthquake activity is important for reinsurance companies and governmental building authorities. They need a complete picture of the possible ...