• by appointment

As a fellow of the German Federal Environmental Foundation, I use my expertise in image processing and machine learning to investigate fascinating and challenging questions in honey bee research.

In current projects, I am investigating how video analysis can be used to accurately determine bee mortality and how the correlation of pollen colors and plant species can be used for biodiversity monitoring.

I am happy to support others with my experience and tools in the automatic color identification of honey bee pollen.

• Machine Learning

• Image Analysis

• Palynology

Publication list

• P. Borlinghaus, R. Odemer, and F. Tausch, ‘Natural color dispersion of corbicular pollen limits color-based classification’, Open Journal of Photogrammetry and Remote Sensing, Mar. 2024 (accepted).
• P. Borlinghaus, J. Jung, and R. Odemer, ‘Introducing Pollenyzer: An App for Automatic Determination of Colour Diversity for Corbicular Pollen Loads’, Smart Agricultural Technology, p. 100263, Jun. 2023, LINK.
• P. Borlinghaus, F. Tausch, and L. Rettenberger, ‘A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris)’, Smart Agricultural Technology, vol. 3, p. 100135, Feb. 2023, LINK.
• P. Borlinghaus, R. Odemer, F. Tausch, K. Schmidt, and O. Grothe, ‘Honey bee counter evaluation – Introducing a novel protocol for measuring daily loss accuracy’, Computers and Electronics in Agriculture, vol. 197, p. 106957, Jun. 2022, LINK.
• P. Borlinghaus and S. Huber, ‘Comparing Apples and Oranges: Human and Computer Clustered Affinity Diagrams Under the Microscope’, in 26th International Conference on Intelligent User Interfaces, in IUI ’21. New York, NY, USA: Association for Computing Machinery, Apr. 2021, pp. 413–422. LINK.