| Evaluating the robustness of semantic segmentation for autonomous driving against real-world adversarial patch attacks F Nesti, G Rossolini, S Nair, A Biondi, G Buttazzo Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 72 | 2022 |
| On the real-world adversarial robustness of real-time semantic segmentation models for autonomous driving G Rossolini, F Nesti, G D’Amico, S Nair, A Biondi, G Buttazzo IEEE Transactions on Neural Networks and Learning Systems, 2023 | 31 | 2023 |
| Falsification-based robust adversarial reinforcement learning X Wang, S Nair, M Althoff 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 23 | 2020 |
| Monitoring safety of autonomous vehicles with crash prediction networks S Nair, S Shafaei, S Kugele, MH Osman, A Knoll The AAAI's Workshop on Artificial Intelligence Safety, 2019 | 9 | 2019 |
| A machine learning based approach to application landscape documentation J Landthaler, Ö Uludağ, G Bondel, A Elnaggar, S Nair, F Matthes The Practice of Enterprise Modeling: 11th IFIP WG 8.1. Working Conference …, 2018 | 8 | 2018 |
| An Evaluation of “Crash Prediction Networks”(CPN) for Autonomous Driving Scenarios in CARLA Simulator S Nair, S Shafaei, D Auge, A Knoll | 2 | 2021 |
| Robust and transferable end-to-end navigation against disturbances and external attacks: an adversarial training approach Z Zhang, S Nair, Z Liu, Y Miao, X Ma Robotic Intelligence and Automation, 2024 | | 2024 |
| Supplementary material for the paper “Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks” F Nesti, G Rossolini, S Nair, A Biondi, G Buttazzo | | |
| Crash Prediction Network: A Plausible Approach to Run-Time Monitoring in Autonomous Vehicles S Nair | | |
