TY - INPR A1 - Sieberichs, Christian A1 - Geerkens, Simon A1 - Braun, Alexander A1 - Waschulzik, Thomas T1 - ECS -- an Interactive Tool for Data Quality Assurance N2 - With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems. KW - Artificial Intelligence KW - Machine Learning KW - PrePrint KW - Systems and Control Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2307.04368 PB - arXiv ER - TY - CHAP A1 - Müller, Patrick A1 - Braun, Alexander T1 - Simulating optical properties to access novel metrological parameter ranges and the impact of different model approximations T2 - 2022 IEEE International Workshop on Metrology for Automotive (MetroAutomotive), 4-6 July 2022 Y1 - 2022 SN - 978-1-6654-6689-9 U6 - https://doi.org/10.1109/MetroAutomotive54295.2022.9855079 SP - 133 EP - 138 PB - IEEE ER - TY - JOUR A1 - Müller, Patrick A1 - Braun, Alexander T1 - Local performance evaluation of AI-algorithms with the generalized spatial recall index JF - tm - Technisches Messen Y1 - 2023 U6 - https://doi.org/10.1515/teme-2023-0013 SN - 2196-7113 VL - 90 IS - 7-8 SP - 464 EP - 477 PB - De Gruyter ER - TY - JOUR A1 - Müller, Patrick A1 - Braun, Alexander T1 - MTF as a performance indicator for AI algorithms? JF - Electronic Imaging: Society for Imaging Science and Technology N2 - Abstract The modulation-transfer function (MTF) is a fundamental optical metric to measure the optical quality of an imaging system. In the automotive industry it is used to qualify camera systems for ADAS/AD. Each modern ADAS/AD system includes evaluation algorithms for environment perception and decision making that are based on AI/ML methods and neural networks. The performance of these AI algorithms is measured by established metrics like Average Precision (AP) or precision-recall-curves. In this article we research the robustness of the link between the optical quality metric and the AI performance metric. A series of numerical experiments were performed with object detection and instance segmentation algorithms (cars, pedestrians) evaluated on image databases with varying optical quality. We demonstrate with these that for strong optical aberrations a distinct performance loss is apparent, but that for subtle optical quality differences – as might arise during production tolerances – this link does not exhibit a satisfactory correlation. This calls into question how reliable the current industry practice is where a produced camera is tested end-of-line (EOL) with the MTF, and fixed MTF thresholds are used to qualify the performance of the camera-under-test. KW - AI performance metrics KW - Artificial Intelligence KW - Modulation Transfer Function (MTF) KW - Optical Quality KW - Perception Y1 - 2023 U6 - https://doi.org/10.2352/EI.2023.35.16.AVM-125 SN - 2470-1173 VL - 35 IS - 16 SP - 1 EP - 7 PB - Society for Imaging Science and Technology ER - TY - CHAP A1 - Tischbein, Franziska A1 - Fatemi, Armin A1 - Wirtz, Frank A1 - Schmoger, Christin A1 - Dorendorf, Stefan A1 - Schurtz, Annika A1 - Echternacht, David A1 - Ulbig, Andreas T1 - Development of Strategies for the Smartification of Low-Voltage Grids T2 - ETG-Fb. 170: ETG Kongress 2023 : Die Energiewende beschleunigen, 25. – 26.05.2023 in Kasse Y1 - 2023 SN - 978-3-8007-6108-1 VL - ETG-Fachberichte 170 SP - 438 EP - 444 PB - VDE CY - Berlin ER - TY - CHAP A1 - Langmann, Reinhard A1 - Stiller, Michael ED - Auer, Michael E. ED - Zutin, Danilo G. T1 - Cloud-based industrial control services - The next generation PLC? T2 - Online Engineering & Internet of Things: Proceedings of the 14th International Conference on Remote Engineering and Virtual Instrumentation REV 2017, held 15–17 March 2017, Columbia University, New York, USA Y1 - 2017 SN - 978-3-319-64351-9 U6 - https://doi.org/10.1007/978-3-319-64352-6_1 SN - 2190-4111 VL - Lecture Notes in Networks and Systems : 22 SP - 3 EP - 18 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Schwung, Dorothea A1 - Yuwono, Steve A1 - Schwung, Andreas A1 - Ding, Steven X. T1 - PLC-Informed Distributed Game Theoretic Learning of Energy-Optimal Production Policies JF - IEEE Transactions on Cybernetics Y1 - 2022 U6 - https://doi.org/10.1109/TCYB.2022.3179950 SN - 2168-2267 SP - 1 EP - 14 PB - IEEE ER - TY - JOUR A1 - Queval, Loic A1 - Sotelo, Guilherme G. A1 - Kharmiz, Yassin A1 - Dias, Daniel H. N. A1 - Sass, Felipe A1 - Zermeno, Victor M. R. A1 - Gottkehaskamp, Raimund T1 - Optimization of the Superconducting Linear Magnetic Bearing of a Maglev Vehicle JF - IEEE Transactions on Applied Superconductivity KW - High temperature superconductors KW - linear magnetic bearing KW - maglev system KW - stochastic optimization KW - superconductor modeling Y1 - 2016 U6 - https://doi.org/10.1109/TASC.2016.2528989 SN - 1051-8223 VL - 26 IS - 3 PB - IEEE ER - TY - JOUR A1 - Langmann, Reinhard A1 - Michael, Stiller T1 - The PLC as a Smart Service in Industry 4.0 Production System JF - Applied Sciences Y1 - 2019 U6 - https://doi.org/10.3390/app9183815 SN - 2076-3417 VL - 9 IS - 18 PB - MDPI ER - TY - JOUR A1 - Echternacht, David A1 - Linnemann, Christian A1 - Drees, Tim A1 - Breuer, Christopher A1 - Moser, Albert T1 - Wechselwirkungen zwischen Druckluftspeichern und Netzengpässen in zukünftigen Energiesystemen JF - Solarzeitalter : Politik, Kultur und Ökonomie erneuerbarer Energien Y1 - 2013 VL - 25 IS - 1 SP - 54 EP - 59 PB - EUROSOLAR Verl. 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