ImageGrains 2.0 dataset
Zenodo (CERN European Organization for Nuclear Research)
Abstract
Images and grain annotations for sediment particles on different imagery types used to train and evaluate the segmentation models of ImageGrains 2.0 (https://github.com/dmair1989/imagegrains). For more details on the data, please refer to the paper. If you use these data, please cite: Mair, D., Witz, G., Do Prado, A., Garefalakis, P., Wild, A., Ville, F., Schuster, B., Horn, M., Österle, J., Fabbri, S. C., Litty, C., Achleitner, S., Leistner, S., Hiller, C., and Schlunegger, F. (2026): ImageGrains 2.0: Improved precision and generalization for grain segmentation, Earth Surf. Dyn., 14, 527-551, https://doi.org/10.5194/esurf-14-527-2026.
Authors 13
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Affiliation as printed
University of Bern
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University of Bern · Universidade de São Paulo
Affiliation as printed
University of Bern
University of Sao Paulo
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Affiliation as printed
University of Bern
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Amanda Wild Aachen
GFZ Helmholtz Centre for Geosciences · RWTH Aachen University
Affiliation as printed
GFZ Helmholtz Centre for Geosciences
RWTH Aachen University
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Affiliation as printed
Universitat de Lleida
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Affiliation as printed
University of Bern
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Victoria University of Wellington · Amt der Vorarlberger Landesregierung
Affiliation as printed
Victoria University of Wellington
Amt der Vorarlberger Landesregierung
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Federal Office of Topography swisstopo
Affiliation as printed
Federal Office of Topography swisstopo
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Federal Office of Topography swisstopo
Affiliation as printed
Federal Office of Topography swisstopo
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Affiliation as printed
Universität Innsbruck
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Affiliation as printed
Universität Innsbruck
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Affiliation as printed
Universität Innsbruck
Geoconsult ZT GmbH
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Affiliation as printed
University of Bern
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