| Machine learning approach to predict aircraft boarding M Schultz, S Reitmann Transportation Research Part C: Emerging Technologies 98, 391-408, 2019 | 46 | 2019 |
| Advanced quantification of weather impact on air traffic management S Reitmann, S Alam, M Schultz ATM Seminar, 20-30, 2019 | 24 | 2019 |
| Blainder—a blender ai add-on for generation of semantically labeled depth-sensing data S Reitmann, L Neumann, B Jung Sensors 21 (6), 2144, 2021 | 20 | 2021 |
| Predictive classification and understanding of weather impact on airport performance through machine learning M Schultz, S Reitmann, S Alam Transportation Research Part C: Emerging Technologies 131, 103119, 2021 | 17 | 2021 |
| Prediction of aircraft boarding time using LSTM network M Schultz, S Reitmann 2018 Winter Simulation Conference (WSC), 2330-2341, 2018 | 16 | 2018 |
| Computation of air traffic flow management performance with long short-term memories considering weather impact S Reitmann, M Schultz Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 12 | 2018 |
| Applying bidirectional long short-term memories (BLSTM) to performance data in air traffic management for system identification S Reitmann, K Nachtigall Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 12 | 2017 |
| Classification of weather impacts on airport operations M Schultz, S Reitmann, S Alam 2019 Winter Simulation Conference (WSC), 500-511, 2019 | 9 | 2019 |
| Performance benchmarking in interdependent ATM systems S Reitmann, A Gillissen, M Schultz Proceedings of the 7th International Conference for Research in Air …, 2016 | 8 | 2016 |
| Consideration of passenger interactions for the prediction of aircraft boarding time M Schultz, S Reitmann Aerospace 5 (4), 101, 2018 | 5 | 2018 |
| Classification of point clouds with neural networks and continuum-type memories S Reitmann, EV Kudryashova, B Jung, V Reitmann Artificial Intelligence Applications and Innovations: 17th IFIP WG 12.5 …, 2021 | 4 | 2021 |
| Prediction of passenger boarding progress using neural network approach M Schultz, S Reitmann 8th International Conference for Research in Air Transportation (ICRAT), 2018 | 3 | 2018 |
| Artificial data analysis in air traffic management S Reitmann, M Schultz CEAS Aeronautical Journal, 2018 | 3 | 2018 |
| Ableitung eines mathematischen Wirkungsmodells durch systematische Analyse von Leistungsindikatoren S Reitmann | 3 | 2017 |
| Developing Generic Flight Schedules for Airport Clusters P Bießlich, S Reitmann, V Gollnick, K Lütjens, K Nachtigall, S Marx 5th CEAS Air and Space Conference, 2015 | 3 | 2015 |
| Generating Synthetic Labeled Data of Animated Fish Swarms in 3D Worlds with Particle Systems and Virtual Sound Wave Sensors S Reitmann, B Jung Cyber-Physical Systems and Control II, 131-140, 2023 | 1 | 2023 |
| Integration of Open Geodata into Virtual Worlds F Richter, S Reitmann, B Jung Proceedings of the 6th International Conference on Virtual and Augmented …, 2022 | 1 | 2022 |
| An Adaptive Framework for Optimization and Prediction of Air Traffic Management (Sub-) Systems with Machine Learning S Reitmann, M Schultz Aerospace 9 (2), 77, 2022 | 1 | 2022 |
| Observation stability and convergence for neural-type evolutionary variational inequalities S Reitmann, B Jung, EV Kudryashova, V Reitmann Differ. Uravn. Protsessy Upr, 126-155, 2021 | 1 | 2021 |
| RoBiMo--The tasks of scientific divers for robot-assisted fresh-water monitoring. S Pose, S Reitmann, G Licht, T Grab, T Fieback FOG-Freiberg Online Geoscience 58, 2021 | 1 | 2021 |
Michael SchultzProfessor, Chair of Air Traffic Concepts, Universität der Bundeswehr MünchenVerified email at unibw.de
