Publications in pub_tas.bib;pub_tas_techreport.bib;pub_lube.bib - Author: Lukas Beer

Copyright Notice: The papers listed below have been published and the copyrights have been transferred to the respective publishers. Therefore, these papers cannot be duplicated for commercial purposes. The following are IEEE's and SPIE's copyright notice; other publishers have similar ones.

9 results
[9]The Good, the Sparse, and the Ugly: Investigating the Impact of Corrupted HD-Map Features on Ego-Vehicle Localization (, and ), In Proceedings of IEEE Intelligent Vehicles Symposium (IV) Workshops, . [bibtex]
[8]Know Your Maps: Uncertainty-Aware Semantic LiDAR Localization with Dual Maps (, and ), In Proceedings of International Conference on Localization and GNSS (ICL-GNSS), . [bibtex]
[7]Vehicle Control in GNSS-Denied Environments Using Map-Based Localization and Model Predictive Control (, , and ), In Proceedings of International Conference on Control and Robotics Engineering (ICCRE), . [bibtex]
[6]Pr├Ązise GNSS-lose Lokalisierung Autonomer Landfahrzeuge im Urbanen und Suburbanen Raum (, and ), In Tagungsband DWT-SGW Forum Unmanned Systems IV, . [bibtex]
[5]GenPa-SLAM: Using a General Panoptic Segmentation for a Real-Time Semantic Landmark SLAM (, and ), In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), . [bibtex] [doi]
[4] General Panoptics: Combining Semantic Segmentation and Classical Methods for a Fast LiDAR Panoptic Segmentation ( and ), In Tagungsband 14. Workshop Fahrerassistenz und automatisiertes Fahren (FAS), Uni-DAS e.V., . [bibtex] [pdf]
[3]Landmark-based methods for locating and navigating autonomous land vehicles in GNSS-denied regions (, , and ), Chapter in Wehrwissenschaftliche Forschung - Jahresbericht 2020, Bundesministerium der Verteidigung, . [bibtex]
[2]Landmarkenbasierte Verfahren zur Lokalisierung und Navigation autonomer Landfahrzeuge in GNS-armen Umgebungen (, , and ), Chapter in Military Scientific Research Annual Report 2020, Bundesministerium der Verteidigung, . [bibtex]
[1] Automatic Generation Of LoD1 City Models And Building Segmentation From Single Aerial Orthographic Images Using Conditional Generative Adversarial Networks (), In GI_Forum 2019, . [bibtex] [pdf] [doi]
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