<?xml version="1.0" encoding="UTF-8" standalone="yes"?><add><doc><field name="objectKind">mycoreobject</field><field name="id">rosdok_disshab_0000002077</field><field name="returnId">rosdok_disshab_0000002077</field><field name="objectProject">rosdok</field><field name="objectType">disshab</field><field name="link">rosdok_derivate_0000067783</field><field name="modified">2023-08-08T10:09:57.463Z</field><field name="created">2019-03-27T08:28:13.425Z</field><field name="modifiedby">administrator</field><field name="createdby">editorD</field><field name="state">published</field><field name="derCount">1</field><field name="derivates">rosdok_derivate_0000067783</field><field name="worldReadable">true</field><field name="worldReadableComplete">true</field><field name="category">derivate_types:fulltext</field><field name="allMeta">Volltext</field><field name="allMeta">fulltext</field><field name="allMeta">wf_edit_epub wf_register_epub</field><field name="category">state:published</field><field name="category.top">state:published</field><field name="allMeta">veröffentlicht</field><field name="allMeta">published</field><field name="allMeta">rosdok/id00002427</field><field name="allMeta">1662425813</field><field name="allMeta">Oau</field><field name="allMeta">2019-03-27</field><field name="allMeta">2023-08-05T19:12:12Z</field><field name="allMeta">rda</field><field name="allMeta">Converted from PICA to MODS using Pica2Mods XSLT Transformer 2.7 [SCM: "0c0e7a3c226a4a0cbcbec39b493c3c5257339ab8" "v2.7" "2023-08-04T00:00:00+0200"] with mode 'DEFAULT'.</field><field name="allMeta">Dissertation</field><field name="allMeta">Hochschulschrift</field><field name="allMeta">Neural text line extraction in historical documents</field><field name="allMeta">a two-stage clustering approach</field><field name="allMeta">Accessibility of the valuable cultural heritage which is hidden in countless scanned historical documents is the motivation for the presented dissertation. 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documents</field><field name="mods.title.subtitle">a two-stage clustering approach</field><field name="mods.nameIdentifier">gnd:1181883350</field><field name="mods.nameIdentifier">gnd:170999645</field><field name="mods.nameIdentifier">orcid:0000-0003-1901-9644</field><field name="mods.nameIdentifier">gnd:38329-6</field><field name="mods.nameIdentifier">gnd:2147083-2</field><field name="mods.nameIdentifier.top">gnd:1181883350</field><field name="mods.nameIdentifier.top">gnd:170999645</field><field name="mods.nameIdentifier.top">orcid:0000-0003-1901-9644</field><field name="mods.nameIdentifier.top">gnd:38329-6</field><field name="mods.nameIdentifier.top">gnd:2147083-2</field><doc><field name="id">rosdok_disshab_0000002077-d496775e55</field><field name="mods.nameIdentifier">gnd:1181883350</field><field name="mods.name">Tobias Grüning</field><field name="mods.name.top">Tobias Grüning</field></doc><doc><field name="id">rosdok_disshab_0000002077-d496775e69</field><field name="mods.nameIdentifier">gnd:170999645</field><field name="mods.nameIdentifier">orcid:0000-0003-1901-9644</field><field name="mods.name">Roger Labahn</field><field name="mods.name.top">Roger Labahn</field></doc><doc><field name="id">rosdok_disshab_0000002077-d496775e85</field><field name="mods.name">Basilis Gatos</field><field name="mods.name.top">Basilis Gatos</field></doc><doc><field name="id">rosdok_disshab_0000002077-d496775e96</field><field name="mods.nameIdentifier">gnd:38329-6</field><field name="mods.name">Universität Rostock</field><field name="mods.name.top">Universität Rostock</field></doc><doc><field name="id">rosdok_disshab_0000002077-d496775e107</field><field name="mods.nameIdentifier">gnd:2147083-2</field><field name="mods.name">Universität Rostock Mathematisch-Naturwissenschaftliche Fakultät</field><field name="mods.name.top">Universität Rostock Mathematisch-Naturwissenschaftliche Fakultät</field></doc><field name="mods.name">Tobias Grüning</field><field name="mods.name">Roger Labahn</field><field name="mods.name">Basilis Gatos</field><field name="mods.name">Universität Rostock</field><field name="mods.name">Universität Rostock Mathematisch-Naturwissenschaftliche Fakultät</field><field name="mods.name.top">Tobias Grüning</field><field name="mods.name.top">Roger Labahn</field><field name="mods.name.top">Basilis Gatos</field><field name="mods.name.top">Universität Rostock</field><field name="mods.name.top">Universität Rostock Mathematisch-Naturwissenschaftliche Fakultät</field><field name="mods.author">Tobias Grüning</field><field name="mods.place">Rostock</field><field name="mods.publisher">Universität Rostock</field><field name="mods.genre">epub.dissertation</field><field name="mods.identifier">http://purl.uni-rostock.de/rosdok/id00002427</field><field name="mods.identifier">info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/READ</field><field name="mods.identifier">urn:nbn:de:gbv:28-rosdok_id00002427-7</field><field name="mods.identifier">10.18453/rosdok_id00002427</field><field name="mods.abstract">Accessibility of the valuable cultural heritage which is hidden in countless scanned historical documents is the motivation for the presented dissertation. The developed (fully automatic) text line extraction methodology combines state-of-the-art machine learning techniques and modern image processing methods. It demonstrates its quality by outperforming several other approaches on a couple of benchmarking datasets. The method is already being used by a wide audience of researchers from different disciplines and thus contributes its (small) part to the aforementioned goal.</field><field name="mods.abstract">Das Erschließen des unermesslichen Wissens, welches in unzähligen gescannten historischen Dokumenten verborgen liegt, bildet die Motivation für die vorgelegte Dissertation. Durch das Verknüpfen moderner Verfahren des maschinellen Lernens und der klassischen Bildverarbeitung wird in dieser Arbeit ein vollautomatisches Verfahren zur Extraktion von Textzeilen aus historischen Dokumenten entwickelt. Die Qualität wird auf verschiedensten Datensätzen im Vergleich zu anderen Ansätzen nachgewiesen. Das Verfahren wird bereits durch eine Vielzahl von Forschern verschiedenster Disziplinen genutzt.</field><field name="mods.dateIssued">2018</field><field name="mods.yearIssued">2018</field><field name="mods.note.referee">Roger Labahn (Universität Rostock, Institut für Mathematik) ; Basilis Gatos (Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”)</field><field name="mods.note.statement of responsibility">vorgelegt von Tobias Grüning</field><field name="mods.type">epub.dissertation</field><field name="search_result_link_text">1
        Gruening_Dissertation_2019.pdf
        
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        rosdok/id000024271662425813Oau2019-03-272023-08-05T19:12:12ZrdaConverted from PICA to MODS using Pica2Mods XSLT Transformer 2.7 [SCM: "0c0e7a3c226a4a0cbcbec39b493c3c5257339ab8" "v2.7" "2023-08-04T00:00:00+0200"] with mode 'DEFAULT'.DissertationHochschulschriftNeural text line extraction in historical documentsa two-stage clustering approachAccessibility of the valuable cultural heritage which is hidden in countless scanned historical documents is the motivation for the presented dissertation. The developed (fully automatic) text line extraction methodology combines state-of-the-art machine learning techniques and modern image processing methods. It demonstrates its quality by outperforming several other approaches on a couple of benchmarking datasets. The method is already being used by a wide audience of researchers from different disciplines and thus contributes its (small) part to the aforementioned goal.Das Erschließen des unermesslichen Wissens, welches in unzähligen gescannten historischen Dokumenten verborgen liegt, bildet die Motivation für die vorgelegte Dissertation. Durch das Verknüpfen moderner Verfahren des maschinellen Lernens und der klassischen Bildverarbeitung wird in dieser Arbeit ein vollautomatisches Verfahren zur Extraktion von Textzeilen aus historischen Dokumenten entwickelt. Die Qualität wird auf verschiedensten Datensätzen im Vergleich zu anderen Ansätzen nachgewiesen. Das Verfahren wird bereits durch eine Vielzahl von Forschern verschiedenster Disziplinen genutzt.TobiasGrüning1986 -VerfasserInaut1181883350RogerLabahn1959 -AkademischeR BetreuerIndgs1709996450000-0003-1901-9644BasilisGatosAkademischeR BetreuerIndgs38329-6Universität Rostock1419 -Grad-verleihende Institutiondgg2147083-2Universität RostockMathematisch-Naturwissenschaftliche FakultätGrad-verleihende Institutiondgghttp://purl.uni-rostock.de/rosdok/id00002427info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/READurn:nbn:de:gbv:28-rosdok_id00002427-710.18453/rosdok_id00002427510 MathematikMathematisch-Naturwissenschaftliche Fakultätalle Rechte vorbehaltenNutzungsrechte erteiltLizenz Metadaten: CC0frei zugänglich (Open Access)en2018Universität RostockRostockmonographic201920182019Universitätsbibliothek RostockRostock2019Universitätsbibliothek Rostockhttp://purl.uni-rostock.de/rosdok/id00002427Roger Labahn (Universität Rostock, Institut für Mathematik) ; Basilis Gatos (Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”)vorgelegt von Tobias Grüning
      
    
  
  
    
      2019-03-27T08:28:13.425Z
      2023-08-08T10:09:57.463Z
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The developed (fully automatic) text line extraction methodology combines state-of-the-art machine learning techniques and modern image processing methods. It demonstrates its quality by outperforming several other approaches on a couple of benchmarking datasets. The method is already being used by a wide audience of researchers from different disciplines and thus contributes its (small) part to the aforementioned goal.</field><field name="mods.abstract">Das Erschließen des unermesslichen Wissens, welches in unzähligen gescannten historischen Dokumenten verborgen liegt, bildet die Motivation für die vorgelegte Dissertation. Durch das Verknüpfen moderner Verfahren des maschinellen Lernens und der klassischen Bildverarbeitung wird in dieser Arbeit ein vollautomatisches Verfahren zur Extraktion von Textzeilen aus historischen Dokumenten entwickelt. Die Qualität wird auf verschiedensten Datensätzen im Vergleich zu anderen Ansätzen nachgewiesen. Das Verfahren wird bereits durch eine Vielzahl von Forschern verschiedenster Disziplinen genutzt.</field><field name="mods.dateIssued">2018</field><field name="mods.yearIssued">2018</field><field name="mods.note.referee">Roger Labahn (Universität Rostock, Institut für Mathematik) ; Basilis Gatos (Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”)</field><field name="mods.note.statement of responsibility">vorgelegt von Tobias Grüning</field><field name="ir.identifier">[xslt]Saxon</field><field name="recordIdentifier">rosdok/id00002427</field><field name="purl">https://purl.uni-rostock.de/rosdok/id00002427</field><field name="ppn">1662425813</field><field name="doi">10.18453/rosdok_id00002427</field><field name="urn">urn:nbn:de:gbv:28-rosdok_id00002427-7</field><field name="ir.creator.result">Tobias Grüning</field><field name="ir.creator.sort">Grüning Tobias</field><field name="ir.title.result">Neural text line extraction in historical documents : a two-stage clustering approach</field><field name="ir.doctype.result">Dissertation</field><field name="ir.doctype_en.result">doctoral thesis</field><field name="ir.originInfo.result">Universität Rostock, 2018</field><field name="ir.abstract300.result">Accessibility of the valuable cultural heritage which is hidden in countless scanned historical documents is the motivation for the presented dissertation. The developed (fully automatic) text line extraction methodology combines state-of-the-art machine learning techniques and modern image…</field><field name="ir.creator_all">Tobias Grüning</field><field name="ir.title_all">Neural text line extraction in historical documents</field><field name="ir.title_all">a two-stage clustering approach</field><field name="ir.location_all">Universitätsbibliothek Rostock</field><field name="ir.location_all">http://purl.uni-rostock.de/rosdok/id00002427</field><field name="ir.creator_all">Tobias</field><field name="ir.creator_all">Grüning</field><field name="ir.creator_all">1986 -</field><field name="ir.creator_all"></field><field name="ir.creator_all">VerfasserIn</field><field name="ir.creator_all">aut</field><field name="ir.creator_all">1181883350</field><field name="ir.creator_all">Roger</field><field name="ir.creator_all">Labahn</field><field name="ir.creator_all">1959 -</field><field name="ir.creator_all"></field><field name="ir.creator_all">AkademischeR BetreuerIn</field><field name="ir.creator_all">dgs</field><field name="ir.creator_all">170999645</field><field name="ir.creator_all">0000-0003-1901-9644</field><field name="ir.creator_all">Basilis</field><field name="ir.creator_all">Gatos</field><field name="ir.creator_all"></field><field name="ir.creator_all">AkademischeR BetreuerIn</field><field name="ir.creator_all">dgs</field><field name="ir.creator_all">38329-6</field><field name="ir.creator_all">Universität Rostock</field><field name="ir.creator_all">1419 -</field><field name="ir.creator_all"></field><field name="ir.creator_all">Grad-verleihende Institution</field><field name="ir.creator_all">dgg</field><field name="ir.creator_all">2147083-2</field><field name="ir.creator_all">Universität Rostock</field><field name="ir.creator_all">Mathematisch-Naturwissenschaftliche Fakultät</field><field name="ir.creator_all"></field><field name="ir.creator_all">Grad-verleihende Institution</field><field name="ir.creator_all">dgg</field><field name="ir.identifier">[purl]http://purl.uni-rostock.de/rosdok/id00002427</field><field name="ir.identifier">[openaire]info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/READ</field><field name="ir.identifier">[urn]urn:nbn:de:gbv:28-rosdok_id00002427-7</field><field name="ir.identifier">[doi]10.18453/rosdok_id00002427</field><field name="ir.oai.setspec.openaire">openaire</field><field name="ir.oai.setspec.open_access">open_access</field><field name="ir.pubyear_start">2018</field><field name="ir.pubyear_end">2018</field><field name="ir.epoch_class.facet">epoch:21th_century</field><field name="ir.language_class.facet">rfc5646:en</field><field name="ir.doctype_class.facet">doctype:epub.dissertation</field><field name="ir.accesscondition_class.facet">accesscondition:openaccess</field><field name="ir.sdnb_class.facet">SDNB:510</field><field name="ir.institution_class.facet">institution:unirostock.mnf</field><field name="ir.state_class.facet">state:published</field></doc></add>