| Estimating the uniqueness of test scenarios derived from recorded real-world-driving-data using autoencoders J Langner, J Bach, L Ries, S Otten, M Holzäpfel, E Sax 2018 IEEE Intelligent Vehicles Symposium (IV), 1860-1866, 2018 | 66 | 2018 |
| A taxonomy and survey on validation approaches for automated driving systems C King, L Ries, J Langner, E Sax 2020 IEEE International Symposium on Systems Engineering (ISSE), 1-8, 2020 | 23 | 2020 |
| Trajectory-based clustering of real-world urban driving sequences with multiple traffic objects L Ries, P Rigoll, T Braun, T Schulik, J Daube, E Sax 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 16 | 2021 |
| A driving scenario representation for scalable real-data analytics with neural networks L Ries, J Langner, S Otten, J Bach, E Sax 2019 IEEE Intelligent Vehicles Symposium (IV), 2215-2222, 2019 | 16 | 2019 |
| Towards a data engineering process in data-driven systems engineering P Petersen, H Stage, J Langner, L Ries, P Rigoll, CP Hohl, E Sax 2022 IEEE International Symposium on Systems Engineering (ISSE), 1-8, 2022 | 11 | 2022 |
| Automated function assessment in driving scenarios C King, L Ries, C Kober, C Wohlfahrt, E Sax 2019 12th IEEE Conference on Software Testing, Validation and Verification …, 2019 | 11 | 2019 |
| Collection of Requirements and Model-based Approach for Scenario Description. T Braun, L Ries, F Körtke, LR Turner, S Otten, E Sax VEHITS, 634-645, 2021 | 9 | 2021 |
| Semantic comparison of driving sequences by adaptation of word embeddings L Ries, M Stumpf, J Bach, E Sax 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 9 | 2020 |
| Scalable Data Set Distillation for the Development of Automated Driving Functions P Rigoll, L Ries, E Sax 2022 IEEE 25th International Conference on Intelligent Transportation …, 2022 | 5 | 2022 |
| Maneuver-based Visualization of Similarities between Recorded Traffic Scenarios. T Braun, L Ries, M Hesche, S Otten, E Sax DATA, 236-244, 2022 | 4 | 2022 |
| Analysis and comparison of datasets by leveraging data distributions in latent spaces H Stage, L Ries, J Langner, S Otten, E Sax Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 3 | 2022 |
| Unveiling objects with sola: An annotation-free image search on the object level for automotive data sets P Rigoll, J Langner, L Ries, E Sax 2024 IEEE Intelligent Vehicles Symposium (IV), 1053-1059, 2024 | 2 | 2024 |
| Focus on the Challenges: Analysis of a User-friendly Data Search Approach with CLIP in the Automotive Domain P Rigoll, P Petersen, H Stage, L Ries, E Sax 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 2 | 2023 |
| Occurrence Estimation for the Classification and Prioritization of Concrete Scenarios in the Context of Virtual Scenario-Based Validation of Vehicles J Fuchs, L Ries, E Sax International Stuttgart Symposium, 109-123, 2024 | | 2024 |
| CLIPping the Limits: Finding the Sweet Spot for Relevant Images in Automated Driving Systems Perception Testing P Rigoll, L Adolph, L Ries, E Sax arXiv preprint arXiv:2404.05309, 2024 | | 2024 |
| The Machine Vision Iceberg Explained: Advancing Dynamic Testing by Considering Holistic Environmental Circumstances H Padusinski, T Braun, C Steinhauser, L Ries, E Sax arXiv preprint arXiv:2401.14831, 2024 | | 2024 |
| A Review of Scenario Similarity Measures for Validation of Highly Automated Driving T Braun, J Fuchs, F Reisgys, L Ries, J Plaum, B Schütt, E Sax 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | | 2023 |
Eric SaxKarlsruhe Institute for TechnologyBestätigte E-Mail-Adresse bei kit.edu
