@article{LangmannMichael2019, author = {Langmann, Reinhard and Michael, Stiller}, title = {The PLC as a Smart Service in Industry 4.0 Production System}, series = {Applied Sciences}, volume = {9}, journal = {Applied Sciences}, number = {18}, publisher = {MDPI}, issn = {2076-3417}, doi = {10.3390/app9183815}, year = {2019}, language = {en} } @article{LyalinaLangmannKrisilov2011, author = {Lyalina, Yuliya and Langmann, Reinhard and Krisilov, V.}, title = {The Interaction Model in iLearning Environments and its Use in the Smart Lab Concept}, series = {International Journal of Online Engineering}, volume = {7}, journal = {International Journal of Online Engineering}, number = {4}, publisher = {iJOE}, doi = {10.3991/ijoe.v7i4.1793}, year = {2011}, language = {en} } @article{MuellerBrummelBraun2021, author = {M{\"u}ller, Patrick and Brummel, Mattis and Braun, Alexander}, title = {Spatial recall index for machine learning algorithms}, series = {London Imaging Meeting}, volume = {2021}, journal = {London Imaging Meeting}, number = {1}, publisher = {Society for Imaging Science and Technology}, isbn = {0-89208-346-6}, doi = {10.2352/issn.2694-118X.2021.LIM-58}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-35657}, pages = {58 -- 62}, year = {2021}, abstract = {We present a novel metric Spatial Recall Index to assess the performance of machine-learning (ML) algorithms for automotive applications, focusing on where in the image which performance occurs. Typical metrics like intersection-over-union (IoU), precisionrecallcurves or average precision (AP) quantify the performance over a whole database of images, neglecting spatial performance variations. But as the optics of camera systems are spatially variable over the field of view, the performance of ML-based algorithms is also a function of space, which we show in simulation: A realistic objective lens based on a Cooke-triplet that exhibits typical optical aberrations like astigmatism and chromatic aberration, all variable over field, is modeled. The model is then applied to a subset of the BDD100k dataset with spatially-varying kernels. We then quantify local changes in the performance of the pre-trained Mask R-CNN algorithm. Our examples demonstrate the spatial dependence of the performance of ML-based algorithms from the optical quality over field, highlighting the need to take the spatial dimension into account when training ML-based algorithms, especially when looking forward to autonomous driving applications.}, language = {en} } @article{BrummelMuellerBraun2022, author = {Brummel, Mattis and M{\"u}ller, Patrick and Braun, Alexander}, title = {Spatial precision and recall indices to assess the performance of instance segmentation algorithms}, series = {Electronic Imaging}, volume = {34}, journal = {Electronic Imaging}, number = {16}, publisher = {Society for Imaging Science and Technology}, issn = {2470-1173}, doi = {10.2352/EI.2022.34.16.AVM-101}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-41552}, pages = {1 -- 6}, year = {2022}, language = {en} } @inproceedings{MuellerLehmannBraun2020, author = {Mueller, Patrick and Lehmann, Matthias and Braun, Alexander}, title = {Simulating tests to test simulation}, series = {IS\&T International Symposium on Electronic Imaging 2020: Autonomous Vehicles and Machines, 26 January 2020 — 30 January 2020, Burlingame, CA, USA}, volume = {2020}, booktitle = {IS\&T International Symposium on Electronic Imaging 2020: Autonomous Vehicles and Machines, 26 January 2020 — 30 January 2020, Burlingame, CA, USA}, number = {16}, publisher = {Society for Imaging Science and Technology}, doi = {10.2352/ISSN.2470-1173.2020.16.AVM-149}, year = {2020}, language = {en} } @article{WittpahlZakourLehmannetal.2018, author = {Wittpahl, Christian and Zakour, Hatem Ben and Lehmann, Matthias and Braun, Alexander}, title = {Realistic Image Degradation with Measured PSF}, series = {Electronic Imaging, Autonomous Vehicles and Machines 2018}, journal = {Electronic Imaging, Autonomous Vehicles and Machines 2018}, number = {17}, publisher = {Society for Imaging Science and Technology}, issn = {2470-1173}, doi = {10.2352/ISSN.2470-1173.2018.17.AVM-149}, pages = {149}, year = {2018}, language = {en} } @article{GeerkensSieberichsBraunetal.2024, author = {Geerkens, Simon and Sieberichs, Christian and Braun, Alexander and Waschulzik, Thomas}, title = {QI²: an interactive tool for data quality assurance}, series = {AI and Ethics}, journal = {AI and Ethics}, publisher = {Springer Nature}, issn = {2730-5961}, doi = {10.1007/s43681-023-00390-6}, year = {2024}, abstract = {The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.}, language = {en} } @unpublished{GeerkensSieberichsBraunetal.2023, author = {Geerkens, Simon and Sieberichs, Christian and Braun, Alexander and Waschulzik, Thomas}, title = {QI2 -- an Interactive Tool for Data Quality Assurance}, address = {arXiv}, year = {2023}, abstract = {The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well known MNIST data set based an handwritten digits.}, language = {en} } @article{LangmannRojasPena2016, author = {Langmann, Reinhard and Rojas-Pe{\~n}a, Leandro}, title = {PLCs as Industry 4.0 Components in Laboratory Applications}, series = {International Journal of Online Engineering}, volume = {12}, journal = {International Journal of Online Engineering}, number = {7}, publisher = {iJOE}, issn = {1861-2121}, doi = {10.3991/ijoe.v12i07.5828}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-28089}, pages = {37}, year = {2016}, language = {en} } @article{WohlersMuellerBraun2022, author = {Wohlers, Luis Constantin and M{\"u}ller, Patrick and Braun, Alexander}, title = {Original image noise reconstruction for spatially-varying filtered driving scenes}, series = {Electronic Imaging: Society for Imaging Science and Technology}, volume = {34}, journal = {Electronic Imaging: Society for Imaging Science and Technology}, number = {16}, publisher = {Society for Imaging Sciences and Technology}, issn = {2470-1173}, doi = {10.2352/EI.2022.34.16.AVM-214}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-41479}, pages = {1 -- 7}, year = {2022}, language = {en} } @inproceedings{FatemiTischbeinWirtzetal.2023, author = {Fatemi, Armin and Tischbein, Franziska and Wirtz, Frank and Schmoger, Christin and Dorendorf, Stefan and Schurtz, Annika and Echternacht, David and Ulbig, Andreas}, title = {On the Impact of Smartification Strategies for the State Estimation of Low Voltage Grids}, series = {13th "Internationale Energiewirtschaftstagung" (IEWT2023), February 15-17, 2023, Vienna, Austria}, booktitle = {13th "Internationale Energiewirtschaftstagung" (IEWT2023), February 15-17, 2023, Vienna, Austria}, address = {Wien}, doi = {10.48550/arXiv.2303.07964}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-41282}, pages = {1 -- 15}, year = {2023}, abstract = {The decarbonization of for example the energy or heat sector leads to the transformation of distribution grids. The expansion of decentralized energy resources and the integration of new consumers due to sector coupling (e.g. heat pumps or electric vehicles) into low voltage grids increases the need for grid expansion and usage of flexibilities in the grid. A high observability of the current grid status is needed to perform these tasks efficiently and effectively. Therefore, there is a need to increase the observability of low voltage grids by installing measurement technologies (e.g. smart meters). Multiple different measurement technologies are available for low voltage grids which can vary in their benefit to observation quality and their installation costs. Therefore, Bayernwerk Netz GmbH and E.DIS AG in cooperation with E-Bridge Consulting GmbH and the Institute for High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW) investigated the effectiveness of different strategies for the smartification of low voltage grids. This paper presents the methodology used for the investigation and exemplary results focusing on the impact of intelligent cable distribution cabinets and smart meters on the quality of the state estimation.}, language = {en} } @article{WolfUlrichBraun2023, author = {Wolf, Dominik Werner and Ulrich, Markus and Braun, Alexander}, title = {Novel developments of refractive power measurement techniques in the automotive world}, series = {Metrologia}, journal = {Metrologia}, number = {ACCEPTED MANUSCRIPT}, publisher = {IOP Publishing}, issn = {1681-7575}, doi = {10.1088/1681-7575/acf1a4}, year = {2023}, abstract = {Refractive power measurements serve as the primary quality standard in the automotive glazing industry. In the light of autonomous driving new optical metrics are becoming more and more popular for specifying optical quality requirements for the windshield. Nevertheless, the link between those quantities and the refractive power needs to be established in order to ensure a holistic requirement profile for the windshield. As a consequence, traceable high-resolution refractive power measurements are still required for the glass quality assessment. Standard measurement systems using Moir{\´e} patterns for refractive power monitoring in the automotive industry are highly resolution limited, wherefore they are insufficient for evaluating the camera window area. Consequently, there is a need for more sophisticated refractive power measurement systems that provide a higher spatial resolution. In addition, a calibration procedure has to be developed in order to guarantee for comparability of the measurement results. For increasing the resolution, a measurement setup based on an auto-correlation algorithm is tested in this paper. Furthermore, a calibration procedure is established by using a single reference lens with a nominal refractive power of 100 km-1. For the calibration of the entire measurement range of the system, the lens is tilted by an inclination angle orthogonal to the optical axis. The effective refractive power is then given by the Kerkhof model. By adopting the measurement and calibration procedure presented in this paper, glass suppliers in the automotive industry will be able to detect relevant manufacturing defects within the camera window area more accurately paving the way for a holistic quality assurance of the windshield for future advanced driver-assistance system (ADAS) functionalities. Concurrently, the traceability of the measurement results is ensured by establishing a calibration chain based on a single reference lens, which is traced back to international standards.}, language = {en} } @article{MuellerBraun2023, author = {M{\"u}ller, Patrick and Braun, Alexander}, title = {MTF as a performance indicator for AI algorithms?}, series = {Electronic Imaging: Society for Imaging Science and Technology}, volume = {35}, journal = {Electronic Imaging: Society for Imaging Science and Technology}, number = {16}, publisher = {Society for Imaging Sciences and Technology}, issn = {2470-1173}, doi = {10.2352/EI.2023.35.16.AVM-125}, pages = {1 -- 7}, year = {2023}, abstract = {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.}, language = {en} } @article{LangmannStiller2015, author = {Langmann, Reinhard and Stiller, Michael}, title = {Industrial Cloud - Status und Ausblick}, series = {HMD Praxis der Wirtschaftsinformatik}, volume = {52}, journal = {HMD Praxis der Wirtschaftsinformatik}, number = {5}, publisher = {Springer Nature}, doi = {10.1365/s40702-015-0162-0}, pages = {647 -- 664}, year = {2015}, language = {de} } @article{KrebsMuellerBraun2021, author = {Krebs, Christian and M{\"u}ller, Patrick and Braun, Alexander}, title = {Impact of Windshield Optical Aberrations on Visual Range Camera Based Classification Tasks Performed by CNNs}, series = {London Imaging Meeting}, volume = {2021}, journal = {London Imaging Meeting}, number = {1}, publisher = {Ingenta connect}, isbn = {0-89208-346-6}, issn = {2694-118X}, doi = {10.2352/issn.2694-118X.2021.LIM-83}, pages = {83 -- 87}, year = {2021}, language = {de} } @inproceedings{MuellerBraunKeuper2022, author = {M{\"u}ller, Patrick and Braun, Alexander and Keuper, Margret}, title = {Impact of realistic properties of the point spread function on classification tasks to reveal a possible distribution shift}, series = {NeurIPS 2022: Workshop on Distribution Shifts: Connecting Methods and Applications, December 3rd, 2022, New Orleans, USA}, booktitle = {NeurIPS 2022: Workshop on Distribution Shifts: Connecting Methods and Applications, December 3rd, 2022, New Orleans, USA}, address = {New Orleans}, year = {2022}, language = {en} } @misc{Kirch2021, author = {Kirch, Marvin Sebastian}, title = {Einstieg in die Thematik und Prototypenbau eines neuronalen Netzes zur Reduktion von manueller Nacharbeit bei der Verkn{\"u}pfung von Daten zu Patienten}, publisher = {Hochschule D{\"u}sseldorf}, address = {D{\"u}sseldorf}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-30016}, pages = {59}, year = {2021}, abstract = {Das Landeskrebsregister (LKR) Nordrhein-Westfalen (NRW) erfasst Daten zu Krebserkrankungen von Patienten von {\"A}rzten, Krankenh{\"a}usern, Pathologien und Melde{\"a}mtern aus ganz NRW um diese auszuwerten. F{\"u}r die Auswertung m{\"u}ssen Daten, die den gleichen Patienten betreffen, zusammen- gef{\"u}hrt werden. Zur Verkn{\"u}pfung gibt es einen automatischen Record-Linkage Algorithmus, der aber bei ca. 5\% aller Meldungen eine manuelle Entscheidung erfordert. Um den Aufwand der manuellen Nachbearbeitung zu reduzieren, soll der Vorgang durch ein k{\"u}nstliches neuronales Netz automatisiert werden. Das k{\"u}nstliches neuronales Netz (KNN) soll mit dem LKR NRW vorliegenden Daten zu manuellen Entscheidungen trainiert werden. Daf{\"u}r m{\"u}ssen die Daten vor der Verwendung umfangreich aufbereitet werden. Das Ziel der Arbeit ist die Aufarbeitung und Aktualisierung eines vorliegenden Konzepts und die Implementierung eines Prototypen des Verfahrens. Der Prototyp soll in der Programmiersprache Java umgesetzt werden. Die folgende Arbeit beginnt mit einer kurzen Einleitung {\"u}ber die Krankheit Krebs, das LKR NRW und KNN. Danach erl{\"a}utere ich die Methodik, die sich mit und die Implementierung des Themas. In der Methodik erkl{\"a}re ich was KNN sind und schneide ihre Funktionsweise an. Außerdem erkl{\"a}re ich wie die Bereitstellung der Daten erfolgt und wie diese f{\"u}r das neuronale Netz verst{\"a}ndlich aufbereitet werden. Zur Implementierung werde ich beschreiben was f{\"u}r eine Entwicklungsumgebung verwendet wurde um das Projekt umzusetzen und wie das Programm umgesetzt wurde. Die Erkl{\"a}rung der Umsetzung besteht aus Unified Modeling Language (UML)-Diagrammen f{\"u}r die Datenaufbereitung und Code-Ausschnitte f{\"u}r die Konfiguration und Schnittstellen des KNN. Das KNN konnte inklusive Datenaufbereitung erstellt werden und klassifiziert 94,4\% der F{\"a}lle korrekt. Auf Grundlage dieser Arbeit kann das Projekt nachgebaut werden.}, language = {de} } @unpublished{SieberichsGeerkensBraunetal.2023, author = {Sieberichs, Christian and Geerkens, Simon and Braun, Alexander and Waschulzik, Thomas}, title = {ECS -- an Interactive Tool for Data Quality Assurance}, publisher = {arXiv}, doi = {10.48550/arXiv.2307.04368}, year = {2023}, abstract = {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.}, language = {en} } @article{Langmann2010, author = {Langmann, Reinhard}, title = {Distributed Web-Based Control System}, series = {International Journal of Online Engineering (iJOE)}, volume = {6}, journal = {International Journal of Online Engineering (iJOE)}, number = {3}, publisher = {iJOE}, doi = {10.3991/ijoe.v6i3.1345}, year = {2010}, language = {en} } @article{MolloyMuellerDeeganetal.2024, author = {Molloy, Dara and M{\"u}ller, Patrick and Deegan, Brian and Mullins, Darragh and Horgan, Jonathan and Ward, Enda and Jones, Edward and Braun, Alexander and Glavin, Martin}, title = {Analysis of the Impact of Lens Blur on Safety-Critical Automotive Object Detection}, series = {IEEE Access}, volume = {12}, journal = {IEEE Access}, publisher = {IEEE}, issn = {2169-3536}, doi = {10.1109/ACCESS.2023.3348663}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-42999}, pages = {3554 -- 3569}, year = {2024}, abstract = {Camera-based object detection is widely used in safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous vehicle research. Road infrastructure has been designed for human vision, so computer vision, with RGB cameras, is a vital source of semantic information from the environment. Sensors, such as LIDAR and RADAR, are also often utilized for these applications; however, cameras provide a higher spatial resolution and color information. The spatial frequency response (SFR), or sharpness of a camera, utilized in object detection systems must be sufficient to allow a detection algorithm to localize objects in the environment over its lifetime reliably. This study explores the relationship between object detection performance and SFR. Six state-of-the-art object detection models are evaluated with varying levels of lens defocus. A novel raw image dataset is created and utilized, containing pedestrians and cars over a range of distances up to 100-m from the sensor. Object detection performance for each defocused dataset is analyzed over a range of distances to determine the minimum SFR necessary in each case. Results show that the relationship between object detection performance and lens blur is much more complex than previous studies have found due to lens field curvature, chromatic aberration, and astigmatisms. We have found that smaller objects are disproportionately impacted by lens blur, and different object detection models have differing levels of robustness to lens blur}, language = {en} } @article{WittpahlDeeganBlacketal.2021, author = {Wittpahl, Christian and Deegan, Brian and Black, Bob and Braun, Alexander}, title = {An analytic-numerical image flicker study to test novel flicker metrics}, series = {Electronic Imaging: Society for Imaging Science and Technology}, journal = {Electronic Imaging: Society for Imaging Science and Technology}, number = {17}, publisher = {Society for Imaging Science and Technology}, issn = {2470-1173}, doi = {10.2352/ISSN.2470-1173.2021.17.AVM-183}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-35671}, pages = {1 -- 8}, year = {2021}, language = {en} }