| What the constant velocity model can teach us about pedestrian motion prediction C Schöller, V Aravantinos, F Lay, A Knoll IEEE Robotics and Automation Letters 5 (2), 1696-1703, 2020 | 120* | 2020 |
| Providentia - A Large Scale Sensing System for the Assistance of Autonomous Vehicles A Krämmer, C Schöller, D Gulati, A Knoll Robotics: Science and Systems (RSS), Workshop on Scene and Situation …, 2019 | 20 | 2019 |
| Targetless Rotational Auto-Calibration of Radar and Camera for Intelligent Transportation Systems C Schöller, M Schnettler, A Krämmer, G Hinz, M Bakovic, M Güzet, A Knoll Intelligent Transportation Systems Conference (ITSC), 2019 | 17 | 2019 |
| Providentia-a large-scale sensor system for the assistance of autonomous vehicles and its evaluation A Krämmer, C Schöller, D Gulati, V Lakshminarasimhan, F Kurz, ... arXiv preprint arXiv:1906.06789, 2019 | 9 | 2019 |
| Towards real-time lifetime prediction of information diffusion I Taxidou, A Alzoghbi, PM Fischer, C Schöller Proceedings of the ACM Web Science Conference, 1-2, 2015 | 3 | 2015 |
| FloMo: Tractable Motion Prediction with Normalizing Flows C Schöller, A Knoll 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 1 | 2021 |
| Vorausschauende Wahrnehmung für sicheres automatisiertes Fahren. Validierung intelligenter Infrastruktursysteme am Beispiel von Providentia A Krämmer, C Schöller, F Kurz, D Rosenbaum, A Knoll Internationales Verkehrswesen 72 (1), 2020 | 1 | 2020 |
| Risk-Based Safety Envelopes for Autonomous Vehicles Under Perception Uncertainty J Bernhard, P Hart, A Sahu, C Schöller, MG Cancimance arXiv preprint arXiv:2107.09918, 2021 | | 2021 |
Peter M. FischerProfessor for Databases and Information Systems, CS Department, University of Augsburg, GermanyBestätigte E-Mail-Adresse bei informatik.uni-augsburg.de
