Publications
Journals:
S. Pose, S. Reitmann, G. J. Licht, T. Grab and T. Fieback. “AI-Prepared Autonomous Freshwater Monitoring and Sea Ground Detection by an Autonomous Surface Vehicle”. In: Remote Sensing. 2023; 15(3):860. DOI: 10.3390/rs15030860. URL: https://www.mdpi.com/2114402
S. Reitmann, M. Schultz. “An Adaptive Framework for Optimization and Prediction of Air Traffic Management (Sub-)Systems with Machine Learning”. In: Aerospace. 2022; 9(2):77. DOI: 10.3390/aerospace9020077. URL: https://www.mdpi.com/2226-4310/9/2/77
S. Reitmann, B. Jung, E. V. Kudryashova and V. Reitmann. “Observation Stability and Convergence for Neural-type Evolutionary Variational Inequalities”. In: Differential Equations and Control Processes N.2 (2021). ISSN: 1817-2172. URL: https://diffjournal.spbu.ru/pdf/21208-jdecp-reitmann.pdf
S. Reitmann, L. Neumann and B. Jung. “BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data”. In: Sensors 21.6 (2021). ISSN: 1424-8220. DOI: 10.3390/s21062144. URL: https://www.mdpi.com/1424-8220/21/6/2144.
M. Schultz, S. Reitmann and S. Alam, “Predictive classification and understanding of weather impact on airport performance through machine learning”. In: Transportation Research Part C: Emerging Technologies 131 (2021), S. 103-119, ISSN 0968-090X, DOI: https://doi.org/10.1016/j.trc.2021.103119.
M. Schultz and S. Reitmann. “Machine learning approach to predict aircraft boarding”. In: Transportation Research Part C: Emerging Technologies 98 (Jan. 2019), S. 391–408. ISSN: 0968-090X. DOI: 10.1016/j.trc.2018.09.007. URL: http://www.sciencedirect.com/science/article/pii/S0968090X18312580.
M. Schultz and S. Reitmann. “Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time”. In: Aerospace 5.4 (Sep. 2018), S. 101. DOI: 10.3390/aerospace5040101. URL: https://www.mdpi.com/2226-4310/5/4/101.
Conference Proceedings:
F. Heisel, L. Kulke, Z. Beek, S. Reitmann, and B. Pfleging. 2024. “Pedestrian-Robot Interaction on Sidewalks: External User Interfaces for Mobile Delivery Robots”. In Proceedings of the International Conference on Mobile and Ubiquitous Multimedia (MUM ‘24). Association for Computing Machinery, New York, NY, USA, 365–380. https://doi.org/10.1145/3701571.3701581
S. Reitmann and B. Jung. 2024. “VR-based Assistance System for Semi-Autonomous Robotic Boats”. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24 Companion), March 11–14, 2024, Boulder, CO, USA. ACM, New York, NY, USA, 5 pages. URL: https://doi.org/10.1145/3610978.3640750
S. Reitmann, T. Mihaylova, E. A. Topp, and V. Kyrki. 2024. “Conflict Simulation for Shared Autonomy in Autonomous Driving”. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24 Companion), March 11–14, 2024, Boulder, CO, USA. ACM, New York, NY, USA, 6 pages. URL: https://doi.org/10.1145/3610978.3640589
G. Jäger, G. Licht, N. Seyffer, and S. Reitmann. 2024. VR-Based Teleoperation of Autonomous Vehicles for Operation Recovery. Ada Lett. 43, 2 (December 2023), 25–29. https://doi.org/10.1145/3672359.3672361
S. Reitmann, B. Jung. Generating Synthetic Labeled Data of Animated Fish Swarms in 3D Worlds with Particle Systems and Virtual Sound Wave Sensors. In: Arseniev, D.G., Aouf, N. (eds) Cyber-Physical Systems and Control II. CPS&C 2021. Lecture Notes in Networks and Systems, vol 460. Springer, Cham. (Best Paper Award) URL: https://link.springer.com/chapter/10.1007/978-3-031-20875-1_12
Florian Richter, Stefan Reitmann, and Bernhard Jung. “Integration of Open Geodata into Virtual Worlds”. In: the 6th International Conference on Virtual and Augmented Reality Simulations (ICVARS 2022), March 25–27, 2022, Brisbane, QLD, Australia. ACM, New York, NY, USA 5 Pages. URL: https://doi.org/10.1145/3546607.3546609
S. Reitmann, E. V. Kudryashova, B. Jung und V. Reitmann. “Classification of Point Clouds with Neural Networks and Continuum-Type Memories”. In: Artificial Intelligence Applications and Innovations - AIAI 2021. IFIP Advances in Information and Communication Technology, Band 627, Springer, 2021, S. 505-517. ISBN: 978-3-030-79150-6 DOI: 10.1007/978-3-030-79150-6_40. URL: https://doi.org/10.1007/978-3-030-79150-6_40
S. Reitmann und M. Schultz. “Computation of Air Traffic Flow Management Performance with Long Short-Term Memories Considering Weather Impact”. In: Artificial Neural Networks and Machine Learning – ICANN 2018. Bd. 11140. Lecture Notes in Computer Science. Springer, 2018, S. 532–541. ISBN: 978-3-030-01421-6. DOI: 10.1007/978-3-030-01421-6_51. URL: http://dx.doi.org/10.1007/978-3-030-01421-6_51.
S. Reitmann und K. Nachtigall. “Applying Bidirectional Long Short-Term Memories (BLSTM) to Performance Data in Air Traffic Management for System Identification.” In: ICANN (2). Hrsg. von Alessandra Lintas u. a. Bd. 10614. Lecture Notes in Computer Science. Springer, 2017, S. 528–536. ISBN: 978-3-319-68612-7. URL: https://doi.org/10.1007/978-3-319-68612-7_60.
Theses:
S. Reitmann. “Künstliche neuronale Netze im leistungsbasierten Luftverkehrsmanagement”. Diss. TU Dresden, 2020. URL: https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-729299.
S. Reitmann. Entwicklung einer Methodik zur Erstellung generischer Flugpläne für Flughafencluster. 2015.
S. Reitmann. Entwicklung eines Modells zum Vergleich von Flugprofilen unter Berücksichtigung stochastischer Störgrößen. 2014.