| Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision F Geissler, S Qutub, S Roychowdhury, A Asgari, Y Peng, A Dhamasia, ... arXiv preprint arXiv:2108.07019, 2021 | 17 | 2021 |
| DNN analysis through synthetic data variation Q Syed Sha, O Grau, K Hagn Proceedings of the 4th ACM Computer Science in Cars Symposium, 1-10, 2020 | 11 | 2020 |
| Hardware Faults that Matter: Understanding and Estimating the Safety Impact of Hardware Faults on Object Detection DNNs S Qutub, F Geissler, Y Peng, R Gräfe, M Paulitsch, G Hinz, A Knoll International Conference on Computer Safety, Reliability, and Security, 298-318, 2022 | 10 | 2022 |
| A Variational Deep Synthesis Approach for Perception Validation O Grau, K Hagn, QS Sha Deep Neural Networks and Data for Automated Driving, pp 359–381, 2022 | 7 | 2022 |
| A low-cost strategic monitoring approach for scalable and interpretable error detection in deep neural networks F Geissler, S Qutub, M Paulitsch, K Pattabiraman International Conference on Computer Safety, Reliability, and Security, 75-88, 2023 | 6 | 2023 |
| Structural coding: A low-cost scheme to protect cnns from large-granularity memory faults A Asgari Khoshouyeh, F Geissler, S Qutub, M Paulitsch, P Nair, ... Proceedings of the International Conference for High Performance Computing …, 2023 | 4 | 2023 |
| Large-scale application of fault injection into pytorch models-an extension to pytorchfi for validation efficiency R Gräfe, QS Sha, F Geissler, M Paulitsch 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems …, 2023 | 4 | 2023 |
| BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture SS Qutub, N Kose, R Rosales, M Paulitsch, K Hagn, F Geissler, Y Peng, ... BMVC 2023, 2023 | 1 | 2023 |
| Deployment of autonomous vehicles F Geissler, R Rosales, NK Cihangir, R Graefe, S Qutub, A Baldovin, ... US Patent App. 17/129,770, 2021 | 1 | 2021 |
| Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models QS Sha, M Paulitsch, K Pattabiraman, K Hagn, F Oboril, C Buerkle, ... arXiv preprint arXiv:2406.03229, 2024 | | 2024 |
| Proactive mitigation of potential object state degradation F Oboril, C Buerkle, P Mudgal, F Pasch, S Qutub, KU Scholl US Patent App. 18/395,849, 2024 | | 2024 |
| Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection SS Qutub, M Paulitsch, KU Scholl, NK Cihangir, K Hagn, F Oboril, G Hinz, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Training neural network with budding ensemble architecture based on diversity loss SS Qutub, RR Neslihan Kose US Patent App. 18/457,002, 2023 | | 2023 |
| Design and Development of Energy Conservative Home Automation System V Shivani, S Sha, MS Swamy International Journal of Computer Applications 975, 8887, 0 | | |
Michael PaulitschIntelBestätigte E-Mail-Adresse bei intel.com
