| Enabling of predictive maintenance in the brownfield through low-cost sensors, an IIoT-architecture and machine learning P Strauß, M Schmitz, R Wöstmann, J Deuse 2018 IEEE International conference on big data (big data), 1474-1483, 2018 | 104 | 2018 |
| Deep reinforcement learning for robotic control in high-dexterity assembly tasks—a reward curriculum approach L Leyendecker, M Schmitz, HA Zhou, V Samsonov, M Rittstieg, D Lütticke International Journal of Semantic Computing 16 (03), 381-402, 2022 | 20 | 2022 |
| Towards real-world force-sensitive robotic assembly through deep reinforcement learning in simulations M Hebecker, J Lambrecht, M Schmitz 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2021 | 18 | 2021 |
| Enabling Rewards for Reinforcement Learning in Laser Beam Welding processes through Deep Learning M Schmitz, F Pinsker, A Ruhri, B Jiang, G Safronov 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 7 | 2020 |
| Verifying the applicability of synthetic image generation for object detection in industrial quality inspection M Shirazi, M Schmitz, S Janssen, A Thies, G Safronov, A Rizk, P Mayr, ... 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 3 | 2021 |
| Machine Learning in Industrial Applications: Insights Gained from Selected Studies M Schmitz Dissertation, Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg …, 2022 | 2 | 2022 |
| Toward fault detection in industrial welding processes with deep learning and data augmentation J Antony, F Schlather, G Safronov, M Schmitz, K Van Laerhoven arXiv preprint arXiv:2106.10160, 2021 | 1 | 2021 |
| An Application-centric Perspective on Industrial Artificial Intelligence M Schmitz, D Yesilbas AMCIS 2022 Proceedings 11, 11, 2022 | | 2022 |
Jens LambrechtJuniorprofessor, Technische Universität BerlinZweryfikowany adres z tu-dortmund.de