The EuroCropsML time series benchmark dataset for few-shot crop type classification in Europe
by Jan Macdonald, Lorenz Richter, Joanna Reuss, Simon Becker, Marco Körner
Year:
2025
Publication:
Nature Scientific Data (12)
Abstract:
We introduce EuroCropsML, an analysis-ready remote sensing dataset based on the open-source EuroCrops collection, for machine learning (ML) benchmarking of time series crop type classification in Europe.
Link:
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Brief introduction of the dida co-author(s) and relevance for dida's ML developments.
Lorenz Richter (PhD)
With an original focus on stochastics and numerics (FU Berlin), the mathematician has been dealing with deep learning algorithms for some time now. Besides his interest in the theory, he has practically solved multiple data science problems in the last 10 years. Lorenz leads the machine learning team.
Jan Macdonald (PhD)
During his studies in mathematics (TU Berlin) Jan focussed on applied topics in optimization, functional analysis, and image processing. His doctoral studies (TU Berlin) explored the interplay between theoretical and empirical research on neural networks. This resulted in his PhD thesis investigating the reliability of deep learning for imaging and computer vision tasks in terms of interpretability, robustness, and accuracy. At dida he works as a Machine Learning Researcher at the interface of scientific research and software development.