City Foundation Models for Learning General Purpose Representations from OpenStreetMap

Balsebre, P., Huang, W. orcid.org/0000-0002-3208-4208, Cong, G. et al. (1 more author) (2024) City Foundation Models for Learning General Purpose Representations from OpenStreetMap. In: CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. 33rd ACM International Conference on Information and Knowledge Management, 21-25 Oct 2024, Boise, USA. Association for Computing Machinery (ACM) , pp. 87-97. ISBN 9798400704369

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Item Type: Proceedings Paper
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© 2024 Copyright held by the owner/author(s). This is an open access conference paper under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: geospatial data, foundation models, contrastive learning
Dates:
  • Published: 21 October 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 13 Mar 2025 13:39
Last Modified: 13 Mar 2025 13:39
Status: Published
Publisher: Association for Computing Machinery (ACM)
Identification Number: 10.1145/3627673.3679662
Open Archives Initiative ID (OAI ID):

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