February 20, 2023 Other Open Access

Ángela Justamante; Alexis Joly; Jean-Christophe Lombardo; Fabian Robert; Mathias Chouet; Sonia Liñán; karen Soacha; Jaume Piera

DataCite XML Export

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  <identifier identifierType="DOI">10.5281/zenodo.7657640</identifier>
  <creators>
    <creator>
      <creatorName>Ángela Justamante</creatorName>
      <affiliation>CREAF</affiliation>
    </creator>
    <creator>
      <creatorName>Alexis Joly</creatorName>
      <affiliation>Inria</affiliation>
    </creator>
    <creator>
      <creatorName>Jean-Christophe Lombardo</creatorName>
      <affiliation>Inria</affiliation>
    </creator>
    <creator>
      <creatorName>Fabian Robert</creatorName>
      <affiliation>Inria</affiliation>
    </creator>
    <creator>
      <creatorName>Mathias Chouet</creatorName>
      <affiliation>Inria</affiliation>
    </creator>
    <creator>
      <creatorName>Sonia Liñán</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0431-4683</nameIdentifier>
      <affiliation>ICM-CSIC</affiliation>
    </creator>
    <creator>
      <creatorName>karen Soacha</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4287-1256</nameIdentifier>
      <affiliation>ICM-CSIC</affiliation>
    </creator>
    <creator>
      <creatorName>Jaume Piera</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-5818-9836</nameIdentifier>
      <affiliation>ICM-CSIC</affiliation>
    </creator>
  </creators>
  <titles>
    <title>GBIF-DL: Create a training set on a particular group of living organisms for machine learning applications</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2023</publicationYear>
  <subjects>
    <subject>citizen science</subject>
    <subject>deep learning</subject>
    <subject>AI</subject>
    <subject>artificial intelligence</subject>
    <subject>citizen observatories</subject>
    <subject>training set</subject>
    <subject>automatic species recognition</subject>
    <subject>biodiversity</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2023-02-20</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Other"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/7657640</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.7657639</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/h2020-cos4cloud</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;GBIF-DL is a service that allows users to create a&amp;nbsp;training set on a particular group of living organisms on-demand, i.e. allowing them to solicit specific data, such as images of specific species and/or specific platforms, or images with a sufficient quality of expert validation. For example:&amp;nbsp;A data scientist or a developer who wants to train an&amp;nbsp;artificial intelligence&amp;nbsp;model on a particular group of species using pytorch software will be able to do it very easily. &lt;strong&gt;More information:&lt;/strong&gt;&amp;nbsp;&lt;a href="https://cos4cloud-eosc.eu/services/gbif-dl/"&gt;https://cos4cloud-eosc.eu/services/gbif-dl/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;This service has been developed by Inria in the Cos4Cloud project framework.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;Infographic&amp;#39;s designer: Lucas Wainer.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/863463/">863463</awardNumber>
      <awardTitle>Co-designed Citizen Observatories Services for the EOS-Cloud</awardTitle>
    </fundingReference>
  </fundingReferences>
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