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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{
  "description": "<p>Wu, Z, Li, H., Zipf, A. (2020). From Historical OpenStreetMap data to customized training samples for geospatial machine learning</p>\n\n<p>In: Minghini, M., Coetzee, S., Juh&aacute;sz, 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 <a href=\"https://zenodo.org/communities/sotm-2020\">https://zenodo.org/communities/sotm-2020</a></p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "GIScience Research Group, Heidelberg University", 
      "@type": "Person", 
      "name": "Wu, Zhaoyan"
    }, 
    {
      "affiliation": "GIScience Research Group, Heidelberg University", 
      "@type": "Person", 
      "name": "Li, Hao"
    }, 
    {
      "affiliation": "GIScience Research Group, Heidelberg University", 
      "@type": "Person", 
      "name": "Zipf, Alexander"
    }
  ], 
  "headline": "From Historical OpenStreetMap data to customized training samples for geospatial machine learning", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2020-07-04", 
  "url": "https://zenodo.org/record/3923040", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3923040", 
  "@id": "https://doi.org/10.5281/zenodo.3923040", 
  "@type": "ScholarlyArticle", 
  "name": "From Historical OpenStreetMap data to customized training samples for geospatial machine learning"
}
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