Prof. Dr. Christoph Michael Tholen

Contact

Address (Oldenburg)

Publications

Logic Programming for Developing an Interactive Explainable Naval Decision Support System
Tarek Elmihoub; Christoph Michael Tholen; Lars Nolle; Frederic Theodor Stahl
In: Maryam Alimardani; Tom Lenaerts; André Meyer-Vitali; Joost Vennekens Ann Nowé; Shenghui Wang (Hrsg.). Hybrid Human Artificial Intelligence (HHAI) 2026. International Conference on Hybrid Human-Artificial Intelligence (HHAI-2026), The 5th International Conference on Hybrid Human-Artificial Intelligence, located at HHAI-2026, July 6-10, Brussels, Belgium, Pages 36-49, Frontiers in Artificial…
Measuring and Comparison of the Energy Consumption of Different Machine Learning Methods
Christoph Michael Tholen; Carolin Leluschko; Lars Nolle; Frederic Theodor Stahl
In: Max Bramer; Frederic Theodor Stahl (Hrsg.). Artificial Intelligence XLII. SGAI International Conference on Artificial Intelligence (AI-2025), Cham, Pages 172-184, ISBN 978-3-032-11402-0, Springer Nature Switzerland, 11/2025.
Flash-flood-driven litter accumulation on beaches studied with aerial imagery and machine learning on Sicily’s northeastern coast, southern Italy
Jun Seok Oh; Carolin Leluschko; Christoph Michael Tholen; Marcello Gugliotta
In: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 383, No. 2307, Pages 1-20, The Royal Society, 10/2025.

XAI4SFAS
Intelligentes Assistenzsystem für die teilautonome Schiffsführung
For several years, a clear trend toward greater automation and reduced crew size has been observed in the shipping industry. The main reasons for this are the reduction of hazards, cost savings,…
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…