Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Abstract. The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection i...
Line Harder Clemmensen, David Delgado Gomez, Bjarn...
Exchange of procedural CAD models between heterogeneous CAD systems is still a challenging issue in CAD area. Previously we proposed an approach for effectively constructing synch...
Workflow and business process modeling approaches have become essential for designing service collaborations when developing SOA-based systems. To derive actual executable busines...
Carsten Lohmann, Joel Greenyer, Juanjuan Jiang, Ta...
In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing ...