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        Anomaliedetektion in räumlich-zeitlichen Datensätzen 

        Anneken, Mathias (2023)
        Human support in surveillance tasks is crucial due to the overwhelming amount of sensor data. This work focuses on the development of data fusion methods using the maritime domain as an example. Various anomalies are ...
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        Modellbasierte Entscheidungsunterstützung für Vertraulichkeit und Datenschutz in Geschäftsprozessen 

        Alpers, Sascha (2023)
        Information Confidentiality and Data Protection Networks (ICPN) support process modelers and process managers in not only taking a purely technical view of data protection and confidentiality, but also in taking it into ...
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        Überwachte Methoden für die spektrale Entmischung mit künstlichen neuronalen Netzen 

        Anastasiadis, Johannes (2023)
        In this work, artificial neural networks trained in a supervised manner for spectral unmixing are investigated. For this purpose, a suitable network architecture is determined first. After that, the focus lies on the ...
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        High-Precision Automotive Radar Target Simulation 

        Diewald, Axel (2023)
        Radar target simulators (RTSs) deceive a radar under test (RuT) by creating an artificial environment consisting of virtual radar targets. In this work, new techniques are presented that overcome the rasterization deficiency ...
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        Proceedings of the 2022 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 

        Beyerer, Jürgen; Zander, Tim (2023)
        In August 2022, Fraunhofer IOSB and IES of KIT held a joint workshop in a Schwarzwaldhaus near Triberg. Doctoral students presented research reports and discussed various topics like computer vision, optical metrology, ...
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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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