Conference paper Open Access

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

Wu, Zhaoyan; Li, Hao; Zipf, Alexander


MARC21 XML Export

<?xml version='1.0' encoding='UTF-8'?>
<record xmlns="http://www.loc.gov/MARC21/slim">
  <leader>00000nam##2200000uu#4500</leader>
  <controlfield tag="005">20200704005919.0</controlfield>
  <controlfield tag="001">3923040</controlfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">GIScience Research Group, Heidelberg University</subfield>
    <subfield code="a">Li, Hao</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">GIScience Research Group, Heidelberg University</subfield>
    <subfield code="a">Zipf, Alexander</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="s">65168</subfield>
    <subfield code="z">md5:5f6c41becb56909d6fc2ef6de6a6d593</subfield>
    <subfield code="u">https://zenodo.org/record/3923040/files/4. From Historical OpenStreetMap data to customized training samples for geospatial machine learning.pdf</subfield>
  </datafield>
  <datafield tag="542" ind1=" " ind2=" ">
    <subfield code="l">open</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2020-07-04</subfield>
  </datafield>
  <datafield tag="909" ind1="C" ind2="O">
    <subfield code="p">openaire</subfield>
    <subfield code="p">user-sotm-2020</subfield>
    <subfield code="o">oai:zenodo.org:3923040</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="u">GIScience Research Group, Heidelberg University</subfield>
    <subfield code="a">Wu, Zhaoyan</subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">From Historical OpenStreetMap data to customized training samples for geospatial machine learning</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">user-sotm-2020</subfield>
  </datafield>
  <datafield tag="540" ind1=" " ind2=" ">
    <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield>
    <subfield code="a">Creative Commons Attribution 4.0 International</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="7">
    <subfield code="a">cc-by</subfield>
    <subfield code="2">opendefinition.org</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">&lt;p&gt;Wu, Z, Li, H., Zipf, A. (2020). From Historical OpenStreetMap data to customized training samples for geospatial machine learning&lt;/p&gt;

&lt;p&gt;In: Minghini, M., Coetzee, S., Juh&amp;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 &lt;a href="https://zenodo.org/communities/sotm-2020"&gt;https://zenodo.org/communities/sotm-2020&lt;/a&gt;&lt;/p&gt;</subfield>
  </datafield>
  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="n">doi</subfield>
    <subfield code="i">isVersionOf</subfield>
    <subfield code="a">10.5281/zenodo.3923039</subfield>
  </datafield>
  <datafield tag="024" ind1=" " ind2=" ">
    <subfield code="a">10.5281/zenodo.3923040</subfield>
    <subfield code="2">doi</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">publication</subfield>
    <subfield code="b">conferencepaper</subfield>
  </datafield>
</record>
319
192
views
downloads
All versions This version
Views 319319
Downloads 192192
Data volume 12.5 MB12.5 MB
Unique views 296296
Unique downloads 176176

Share

Cite as