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DOI: 10.4121/6ae9ccb8-9f31-485a-a55a-deb7c400b921

Basting, Mark; Bruintjes, Robert-Jan; Wiedemer, Thaddaüs; Kümmerer, Matthias; Bethge, Matthias et. al. (2025): Data underlying the publication/thesis chapter: Scale Learning in Scale-Equivariant Convolutional Networks. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/6ae9ccb8-9f31-485a-a55a-deb7c400b921.v1

Categories

• Artificial Intelligence and Image Processing
• Information and Computing Sciences

Keywords

Computer Vision Convolutional neural network (CNN) equivariance scale scale distribution scale variation

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

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by Mark Basting, Robert-Jan Bruintjes , Thaddaüs Wiedemer, Matthias Kümmerer, Matthias Bethge, Jan van Gemert

VISAPP article and thesis chapter. This article addresses the mismatch between the scales for which scale equivariance methods are designed, and those occurring in real datasets.

History

• 2025-09-09 first online, published, posted

Publisher

4TU.ResearchData

Format

GitHub repository containing Python code.

Associated peer-reviewed publication

Scale Learning in Scale-Equivariant Convolutional Networks

References

• https://www.scitepress.org/Papers/2024/123798/123798.pdf
• https://www.scitepress.org/Link.aspx?doi=10.5220/0012379800003660

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems, Computer Vision Lab