Conference paper Open Access

From Historical OpenStreetMap data to customized training samples for geospatial machine learning

Wu, Zhaoyan; Li, Hao; Zipf, Alexander


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  <dc:creator>Wu, Zhaoyan</dc:creator>
  <dc:creator>Li, Hao</dc:creator>
  <dc:creator>Zipf, Alexander</dc:creator>
  <dc:date>2020-07-04</dc:date>
  <dc:description>Wu, Z, Li, H., Zipf, A. (2020). From Historical OpenStreetMap data to customized training samples for geospatial machine learning

In: Minghini, M., Coetzee, S., Juhász, L., Yeboah, G., Mooney, P., Grinberger, A.Y. (Eds.). Proceedings of the Academic Track at the State of the Map 2020 Online Conference, July 4-5 2020. Available at https://zenodo.org/communities/sotm-2020</dc:description>
  <dc:identifier>https://zenodo.org/record/3923040</dc:identifier>
  <dc:identifier>10.5281/zenodo.3923040</dc:identifier>
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  <dc:relation>doi:10.5281/zenodo.3923039</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/sotm-2020</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
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  <dc:title>From Historical OpenStreetMap data to customized training samples for geospatial machine learning</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
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