| RadarScenes: A real-world radar point cloud data set for automotive applications O Schumann, M Hahn, N Scheiner, F Weishaupt, JF Tilly, J Dickmann, ... 2021 IEEE 24th International Conference on Information Fusion (FUSION), 1-8, 2021 | 131 | 2021 |
| Seeing around street corners: Non-line-of-sight detection and tracking in-the-wild using doppler radar N Scheiner, F Kraus, F Wei, B Phan, F Mannan, N Appenrodt, W Ritter, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 125 | 2020 |
| Object detection for automotive radar point clouds–a comparison N Scheiner, F Kraus, N Appenrodt, J Dickmann, B Sick AI Perspectives 3 (1), 1-23, 2021 | 46 | 2021 |
| A multi-stage clustering framework for automotive radar data N Scheiner, N Appenrodt, J Dickmann, B Sick 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2060-2067, 2019 | 42 | 2019 |
| Using machine learning to detect ghost images in automotive radar F Kraus, N Scheiner, W Ritter, K Dietmayer 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 41 | 2020 |
| Radar-based feature design and multiclass classification for road user recognition N Scheiner, N Appenrodt, J Dickmann, B Sick 2018 IEEE Intelligent Vehicles Symposium (IV), 779-786, 2018 | 39 | 2018 |
| Radar-based road user classification and novelty detection with recurrent neural network ensembles N Scheiner, N Appenrodt, J Dickmann, B Sick 2019 IEEE Intelligent Vehicles Symposium (IV), 722-729, 2019 | 36 | 2019 |
| Off-the-shelf sensor vs. experimental radar-How much resolution is necessary in automotive radar classification? N Scheiner, O Schumann, F Kraus, N Appenrodt, J Dickmann, B Sick 2020 IEEE 23rd International Conference on Information Fusion (FUSION), 1-8, 2020 | 33 | 2020 |
| Automated ground truth estimation of vulnerable road users in automotive radar data using GNSS N Scheiner, N Appenrodt, J Dickmann, B Sick 2019 IEEE MTT-S International Conference on Microwaves for Intelligent …, 2019 | 16 | 2019 |
| The Radar Ghost Dataset–An Evaluation of Ghost Objects in Automotive Radar Data F Kraus, N Scheiner, W Ritter, K Dietmayer 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 14 | 2021 |
| Automated ground truth estimation for automotive radar tracking applications with portable GNSS and IMU devices N Scheiner, S Haag, N Appenrodt, B Duraisamy, J Dickmann, M Fritzsche, ... 2019 20th International Radar Symposium (IRS), 1-10, 2019 | 12 | 2019 |
| Radar for Autonomous Driving–Paradigm Shift from Mere Detection to Semantic Environment Understanding J Dickmann, J Lombacher, O Schumann, N Scheiner, SK Dehkordi, ... Fahrerassistenzsysteme 2018: Von der Assistenz zum automatisierten Fahren 4 …, 2019 | 11 | 2019 |
| New Challenges for Deep Neural Networks in Automotive Radar Perception N Scheiner, F Weishaupt, JF Tilly, J Dickmann Automatisiertes Fahren 2020, 165-182, 2021 | 6* | 2021 |
| Machine Learning Concepts For Multiclass Classification Of Vulnerable Road Users N Scheiner, O Schumann 16th European Radar Conference (EuRAD 2019) Workshops, 2019 | 2 | 2019 |
| Object Detection for Automotive Radar Perception NS Scheiner University of Kassel, 2024 | | 2024 |
| System und Verfahren zum komfortablen Betrieb eines Fahrzeugs N Scheiner DE Patent DE102023001830A1, 2024 | | 2024 |
| Vorrichtung und Verfahren zur Erfassung einer Fahrzeugumgebung N Scheiner DE Patent DE102023000939A1, 2023 | | 2023 |
| Verfahren und Vorrichtung zur Kommunikation eines Fahrzeuges mit Verkehrsteilnehmern N Scheiner, J Haase, M Steiner, J Tilly DE Patent DE102022002990A1, 2022 | | 2022 |
| Verfahren zur Segmentierung mehrdimensionaler Messpunkte N Scheiner DE Patent DE102021002217A1, 2021 | | 2021 |
| Verfahren zur Umgebungserfassung N Scheiner, F Kraus DE Patent DE102021001452A1, 2021 | | 2021 |
Bernhard SickProfessor of Intelligent Embedded Systems, University of KasselBestätigte E-Mail-Adresse bei uni-kassel.de
