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Teja Kattenborn

2 papers indexed

arxivcs.LG2026-07-22

STeMP: Spatio-Temporal Modelling Protocol

Jan Linnenbrink, Jakub Nowosad, Marvin Ludwig, Anna Frederike Jablotschkin, Fabian Schumacher, Teja Kattenborn, et al.

Spatio-temporal machine-learning modelling is an important tool in environmental research. However, machine-learning models are highly sensitive to both the characteristics of the training data, such as its distribution, and methodological choices, including the cross-validation…

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arxivcs.CV2026-06-25

SelectAnyTree: A Promptable Instance Segmentation Model for 3D Forest LiDAR Point Clouds

Trung Thanh Nguyen, Daniel Lusk, Kilian Gerberding, Janusch Vajna-Jehle, Tuan-Anh Vu, Duc Viet Le, et al.

Automated instance segmentation of forest LiDAR point clouds is increasingly critical as forest monitoring moves toward scalable, detailed, 3D measurement. Yet, progress is constrained by label scarcity for tree instances; a single hectare can hold millions of points and hundreds…

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