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Acting Head of the Research Department Marine Perception

Dr. Frederic Theodor Stahl

Organizational unit Marine Perception
Contact +49 441 99833 4713 (Oldenburg)

https://fredericstahl.wordpress.com/
Address (Oldenburg) Technologie- und Gründerzentrum OldenburgMarie-Curie-Str. 1D-26129 Oldenburg

Publications

A benchmark and survey of fully unsupervised concept drift detectors on real-world data streams

Daniel Lukats; Oliver Zielinski; Axel Hahn; Frederic Theodor Stahl

In: International Journal of Data Science and Analytics, Vol. 18, No. 3, Pages 1-31, Springer Nature, Switzerland, 8/2024.

To the publication

On Object Detection and Explainability with Sonar Imagery

Tarek Elmihoub; Abdulhakim El Gadi Gadi; Lars Nolle; Frederic Theodor Stahl

In: 2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA). IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA-2024), May 19-21, Tripoli, Libyan Arab Jamahiriya, Pages 1-8, ISBN 979-8-3503-7263-2, IEEE Xplore, New Jersey, 7/2024.

To the publication

Model Generalisation for Predicting the Amount of Photosynthetically Available Radiation in the Water Column from Freefall Profiler Observations

Christoph Tholen; Lars Nolle; Jochen Wollschläger; Frederic Theodor Stahl

In: ECMS 2024, 38th Proceedings. International Conference on Modelling and Simulation (ECMS-2024), June 4-7, Crakow, Poland, Pages 1-6, ISBN 978-3-937436-84-5, ECMS, United Kingdom, 6/2024.

To the publication
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Profile

  • XAI4SFAS

    Intelligentes Assistenzsystem für die teilautonome Schiffsführung

    Partners

    marinom GmbH

    Jade Hochschule Wilhelmshaven/Oldenburg/Elsfleth

     

  • HAI-x

    Hybrid AI explainer

    More and more industry, business and science applications employ multiple AI techniques and AI workflows to solve complex problems and automate as well as optimise complex processes and…

    HAI-x

  • iMagine

    Imaging data and services for aquatic science

    Aquatic research often relies on image and video data to gain knowledge about our oceans, lakes and rivers. Current challenges in this research area include analyzing human-caused littering or oil…

    iMagine

  • ZLW

    Zukunftslabor Wassermanagement

    Partners

    Beteiligte wissenschaftliche Einrichtungen:

    − Carl von Ossietzky Universität Oldenburg (UOL)

    − Leibniz Universität Hannover (LUH)

    − Technische Universität Braunschweig (TUBS)

    − Technische…

    ZLW

  • APLASTIC-Q-Canada

    Machine Learning identification of pollutants and other debris in Canadian Waterways

    The project deals with the further development of AI methods for the detection and analysis of litter in rivers and canals. Stationary camera systems are used, which enable long-term monitoring of the…

    APLASTIC-Q-Canada
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