1 Ocak 2018 Konferans bildirisi Açık Erişim

Laux, Hendrik; Bytyn, Andreas; Ascheid, Gerd; Schmeink, Anke; Kurt, Gunes Karabulut; Dartmann, Guido

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/32247</identifier>
  <creators>
    <creator>
      <creatorName>Laux, Hendrik</creatorName>
      <givenName>Hendrik</givenName>
      <familyName>Laux</familyName>
      <affiliation>Rhein Westfal TH Aachen, ICE, Aachen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Bytyn, Andreas</creatorName>
      <givenName>Andreas</givenName>
      <familyName>Bytyn</familyName>
      <affiliation>Rhein Westfal TH Aachen, ICE, Aachen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Ascheid, Gerd</creatorName>
      <givenName>Gerd</givenName>
      <familyName>Ascheid</familyName>
      <affiliation>Rhein Westfal TH Aachen, ICE, Aachen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Schmeink, Anke</creatorName>
      <givenName>Anke</givenName>
      <familyName>Schmeink</familyName>
      <affiliation>Rhein Westfal TH Aachen, ISEK, Aachen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Kurt, Gunes Karabulut</creatorName>
      <givenName>Gunes Karabulut</givenName>
      <familyName>Kurt</familyName>
      <affiliation>Istanbul Tech Univ, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Dartmann, Guido</creatorName>
      <givenName>Guido</givenName>
      <familyName>Dartmann</familyName>
      <affiliation>Trier Univ Appl Sci, Trier, Germany</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Learning-Based Indoor Localization For Industrial Applications</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2018</publicationYear>
  <dates>
    <date dateType="Issued">2018-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/32247</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1145/3203217.3203227</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Modern process automation and the industrial evolution heading towards Industry 4.0 require a huge variety of information to be fused in a Cyber-Physical System. Important for many applications is the spatial position of an arbitrary object given directly or indirectly in terms of data that has to be processed to obtain position information. Starting point for the idea of the technical reflection-based sound localization system presented in this paper is the biological role model of humans being able to learn how to localize sound sources. Compared to other forms of sound localization, this nature-inspired method has no need for high spatial and temporal accuracy or big microphone arrays. Possible applications for this system are indoor robot localization or object tracking.</description>
  </descriptions>
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