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Improved Sensor Model for Realistic Synthetic Data Generation., and . CSCS, page 4:1-4:9. ACM, (2021)SynPeDS: A Synthetic Dataset for Pedestrian Detection in Urban Traffic Scenes., , , , , , , , , and . CSCS, page 2:1-2:10. ACM, (2022)VALERIE22 - A photorealistic, richly metadata annotated dataset of urban environments., and . CSCS, page 6:1-6:9. ACM, (2023)DNN Analysis through Synthetic Data Variation., , and . CSCS, page 4:1-4:10. ACM, (2020)Increasing pedestrian detection performance through weighting of detection impairing factors., and . CSCS, page 1:1-1:10. ACM, (2022)Training and Validation of Visual Perception Functions for Autonomous Driving with Synthetic Data.. University of Kiel, Germany, (2024)Towards machine learning-based optimal has, , , , and . arXiv preprint arXiv:1808.08065, (2018)Keep calm and don’t switch: about the relationship between switches and quality in HAS, , , , and . 2017 29th International Teletraffic Congress (ITC 29), 3, page 1--6. IEEE, (2017)Validation of Pedestrian Detectors by Classification of Visual Detection Impairing Factors., and . ECCV Workshops (5), volume 13805 of Lecture Notes in Computer Science, page 476-491. Springer, (2022)BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture., , , , , , , , and . BMVC, page 792-797. BMVA Press, (2023)