| Making the case for safety of machine learning in highly automated driving S Burton, L Gauerhof, C Heinzemann Computer Safety, Reliability, and Security: SAFECOMP 2017 Workshops, ASSURE …, 2017 | 151 | 2017 |
| Structuring validation targets of a machine learning function applied to automated driving L Gauerhof, P Munk, S Burton Computer Safety, Reliability, and Security: 37th International Conference …, 2018 | 64 | 2018 |
| Assuring the safety of machine learning for pedestrian detection at crossings L Gauerhof, R Hawkins, C Picardi, C Paterson, Y Hagiwara, I Habli Computer Safety, Reliability, and Security: 39th International Conference …, 2020 | 42 | 2020 |
| Confidence arguments for evidence of performance in machine learning for highly automated driving functions S Burton, L Gauerhof, BB Sethy, I Habli, R Hawkins Computer Safety, Reliability, and Security: SAFECOMP 2019 Workshops, ASSURE …, 2019 | 36 | 2019 |
| Structuring the safety argumentation for deep neural network based perception in automotive applications G Schwalbe, B Knie, T Sämann, T Dobberphul, L Gauerhof, S Raafatnia, ... Computer Safety, Reliability, and Security. SAFECOMP 2020 Workshops: DECSoS …, 2020 | 27 | 2020 |
| Testing deep learning-based visual perception for automated driving S Abrecht, L Gauerhof, C Gladisch, K Groh, C Heinzemann, M Woehrle ACM Transactions on Cyber-Physical Systems (TCPS) 5 (4), 1-28, 2021 | 21 | 2021 |
| Facer: A universal framework for detecting anomalous operation of deep neural networks C Schorn, L Gauerhof 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 12 | 2020 |
| Fault Injectors for TensorFlow: evaluation of the impact of random hardware faults on deep CNNs M Beyer, A Morozov, E Valiev, C Schorn, L Gauerhof, K Ding, K Janschek arXiv preprint arXiv:2012.07037, 2020 | 11 | 2020 |
| Reverse variational autoencoder for visual attribute manipulation and anomaly detection L Gauerhof, N Gu 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), 2103-2112, 2020 | 10 | 2020 |
| Intelligent and connected cyber-physical systems: A perspective from connected autonomous vehicles W Chang, S Burton, CW Lin, Q Zhu, L Gauerhof, J McDermid Intelligent Internet of Things: From Device to Fog and Cloud, 357-392, 2020 | 6 | 2020 |
| Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers. A Morozov, E Valiev, M Beyer, K Ding, L Gauerhof, C Schorn AISafety@ IJCAI, 2020 | 5 | 2020 |
| Integration of a dynamic model in a driving simulator to meet requirements of various levels of automatization L Gauerhof, A Bilic, C Knies, F Diermeyer 2016 IEEE Intelligent Vehicles Symposium (IV), 292-297, 2016 | 4 | 2016 |
| Automating Safety Argument Change Impact Analysis for Machine Learning Components C Cârlan, L Gauerhof, B Gallina, S Burton 2022 IEEE 27th Pacific Rim International Symposium on Dependable Computing …, 2022 | 3 | 2022 |
| Generation of synthetic lidar signals JN Caspers, J Ebert, L Gauerhof, M Pfeiffer, R Has, T Maurer, A Khoreva US Patent App. 17/009,351, 2021 | 3 | 2021 |
| ADAS for the communication between automated and manually driven cars L Gauerhof, A Kürzl, M Lienkamp 7. Tagung Fahrerassistenzsysteme, 2015 | 3 | 2015 |
| Considering reliability of deep learning function to boost data suitability and anomaly detection L Gauerhof, Y Hagiwara, C Schorn, M Trapp 2020 IEEE International Symposium on Software Reliability Engineering …, 2020 | 2 | 2020 |
| Method, device, and computer program for creating training data in a vehicle C Schorn, L Gauerhof US Patent App. 17/658,323, 2022 | 1 | 2022 |
| Method and device for training a machine learning system L Gauerhof, N Gu US Patent App. 17/610,669, 2022 | 1 | 2022 |
| Method and device for testing the robustness of an artificial neural network L Gauerhof, N Gu US Patent App. 17/596,126, 2022 | 1 | 2022 |
| On the necessity of explicit artifact links in safety assurance cases for machine learning L Gauerhof, R Gansch, C Heinzemann, M Woehrle, A Heyl 2021 IEEE International Symposium on Software Reliability Engineering …, 2021 | 1 | 2021 |
