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Lennart Ries
Lennart Ries
Research Scientist
Verified email at fzi.de
Title
Cited by
Cited by
Year
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
672018
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
232020
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
162021
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
162019
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
122022
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
112019
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
92021
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
92020
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
52022
Maneuver-based Visualization of Similarities between Recorded Traffic Scenarios.
T Braun, L Ries, M Hesche, S Otten, E Sax
DATA, 236-244, 2022
42022
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
32022
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
22024
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
22023
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
12023
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
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