November 29, 2023 Software Closed Access

Starke, Sebastian; Smid, Michal

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  <identifier identifierType="DOI">10.14278/rodare.2586</identifier>
  <creators>
    <creator>
      <creatorName>Starke, Sebastian</creatorName>
      <givenName>Sebastian</givenName>
      <familyName>Starke</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-5007-1868</nameIdentifier>
      <affiliation>HZDR</affiliation>
    </creator>
    <creator>
      <creatorName>Smid, Michal</creatorName>
      <givenName>Michal</givenName>
      <familyName>Smid</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-7162-7500</nameIdentifier>
      <affiliation>HZDR</affiliation>
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  </creators>
  <titles>
    <title>Software: removal of bremsstrahlung background from SAXS signals with deep neural networks</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2023</publicationYear>
  <subjects>
    <subject>SAXS</subject>
    <subject>XFEL</subject>
    <subject>equivariant neural networks</subject>
    <subject>noise removal</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2023-11-29</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/2586</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-37977</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.2585</relatedIdentifier>
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  <version>1</version>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/closedAccess">Closed Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Software for training and inference of neural network models to remove bremsstrahlung background from SAXS imaging data obtained at the European XFEL laboratory.&lt;/p&gt;

&lt;p&gt;We thank Peter Steinbach for providing the codebase for the equivariant UNet, which we integrated into our repository.&lt;/p&gt;</description>
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