| Inspect, understand, overcome: a survey of practical methods for AI safety S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ... Deep Neural Networks and Data for Automated Driving, 3-78, 2022 | 70 | 2022 |
| Using mixture of expert models to gain insights into semantic segmentation S Pavlitskaya, C Hubschneider, M Weber, R Moritz, F Huger, P Schlicht, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 31 | 2020 |
| Modeling and training of neural processing systems E Kusmenko, S Nickels, S Pavlitskaya, B Rumpe, T Timmermanns 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering …, 2019 | 28 | 2019 |
| On the engineering of AI-powered systems E Kusmenko, S Pavlitskaya, B Rumpe, S Stüber 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 19 | 2019 |
| Adversarial attacks on traffic sign recognition: A survey S Pavlitska, N Lambing, JM Zöllner 2023 3rd International Conference on Electrical, Computer, Communications …, 2023 | 17 | 2023 |
| Feasibility and suppression of adversarial patch attacks on end-to-end vehicle control S Pavlitskaya, S Ünver, JM Zöllner 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 16 | 2020 |
| Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection S Pavlitskaya, BM Codău, JM Zöllner AISafety@IJCAI-ECAI-2022, 2022 | 12 | 2022 |
| Sparsely-gated mixture-of-expert layers for CNN interpretability S Pavlitska, C Hubschneider, L Struppek, JM Zöllner 2023 International Joint Conference on Neural Networks (IJCNN), 1-10, 2023 | 10* | 2023 |
| Suppress with a patch: Revisiting universal adversarial patch attacks against object detection S Pavlitskaya, J Hendl, S Kleim, LJ Müller, F Wylczoch, JM Zöllner 2022 International Conference on Electrical, Computer, Communications and …, 2022 | 7 | 2022 |
| CAGE: Circumplex Affect Guided Expression Inference N Wagner, F Mätzler, SR Vossberg, H Schneider, S Pavlitska, JM Zöllner Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 6 | 2024 |
| Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise S Pavlitskaya, J Oswald, JM Zöllner 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1551-1559, 2022 | 6 | 2022 |
| Traffic light recognition using convolutional neural networks: A survey S Pavlitska, N Lambing, AK Bangaru, JM Zöllner 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 5 | 2023 |
| Adversarial vulnerability of temporal feature networks for object detection S Pavlitskaya, N Polley, M Weber, JM Zöllner European Conference on Computer Vision, 510-525, 2022 | 5 | 2022 |
| Evaluating mixture-of-experts architectures for network aggregation S Pavlitskaya, C Hubschneider, M Weber Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 5 | 2022 |
| Adversarial Black-Box Attacks on Vision-based Deep Reinforcement Learning Agents A Tanev, S Pavlitskaya, J Sigloch, A Roennau, R Dillmann, JM Zollner 2021 IEEE International Conference on Intelligence and Safety for Robotics …, 2021 | 4 | 2021 |
| Conditioning Latent-Space Clusters for Real-World Anomaly Classification D Bogdoll, S Pavlitska, S Klaus, JM Zöllner 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 1620-1625, 2023 | 3 | 2023 |
| Low-Power Traffic Surveillance using Multiple RGB and Event Cameras: A Survey T Fleck, S Pavlitska, S Nitzsche, B Pachideh, F Peccia, SH Ahmed, ... 2023 IEEE International Smart Cities Conference (ISC2), 1-7, 2023 | 3 | 2023 |
| Getting ready for all types of users: A virtual reality training center for automated vehicles H Gremmelmaier, L Töttel, S Pavlitskaya, S Orf, M Zofka, JM Zöllner 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 77-85, 2022 | 3 | 2022 |
| Is neuron coverage needed to make person detection more robust? S Pavlitskaya, Ş Yıkmış, JM Zöllner Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
| Hybrid video anomaly detection for anomalous scenarios in autonomous driving D Bogdoll, J Imhof, T Joseph, S Pavlitska, JM Zöllner arXiv preprint arXiv:2406.06423, 2024 | 2 | 2024 |
J. Marius ZöllnerProfessor at Karlsruhe Institute of Technology (KIT), Director at Forschungszentrum Informatik (FZI)Adresse e-mail validée de fzi.de
