Dr. rer. nat. Christoph Tholen

Contact +49 441 99833 4721 (Oldenburg)

Address (Oldenburg) Technologie- und Gründerzentrum OldenburgMarie-Curie-Str. 126129 Oldenburg

Publications

On the Development of a Pixel-Wise Plastic Waste Identification System for Multispectral Remote Sensing Applications
Christoph Tholen; Eike Rodenbäck; Lars Nolle; Robert Rettig; Frederic Stahl
In: Max Bramer; Frederic Stahl (Hrsg.). Artificial Intelligence XLI. SGAI International Conference on Artificial Intelligence (AI-2024), December 17-19, Oxford, United Kingdom, Pages 47-60, ISBN 978-3-031-77915-2, Springer Nature Switzerland, 2025.
Bi-directional LSTM Applied to the Maritime Target Motion Analysis Problem
Lars Nolle; Nils Meinardus; Martin Kumm; Christoph Tholen
In: Artificial Intelligence XLI. SGAI International Conference on Artificial Intelligence (AI-2024), 44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17–19, 2024, Proceedings, Part II, December 17-19, Cambridge, United Kingdom, Pages 270-275, SGAI (SGAI 2024), Vol. 15447, Springer Nature Switzerland, Cham, 11/2024.
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.

XAI4SFAS
Intelligentes Assistenzsystem für die teilautonome Schiffsführung
Partners
marinom GmbH
Jade Hochschule Wilhelmshaven/Oldenburg/Elsfleth
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…
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…
PlasticObs_plus
Verbund - KI: PlasticObs_plus - Maschinelles Lernen auf Multisensordaten der flugzeuggestützten Fernerkundung zur Bekämpfung von Plastikmüll in Meeren und Flüssen
Airborne monitoring for plastic litter detection represents a modern, universal observation method to address the urgent and rapidly increasing problem of plastic litter pollution on a global scale…
MATE
Maritime Traffic Emissions: A monitoring network
Maritime ship traffic is globally increasing with 90% of the world trade being carried over the ocean. The emissions of the maritime traﬃc are a severe threat to the marine environment and coastal…