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Automated Extraction of Icon-based Tables

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dc.contributor.authorThome, Boris
dc.contributor.authorHertweck, Friederike
dc.contributor.authorJonas, Lukas
dc.contributor.authorYasar, Serife
dc.contributor.authorConrad, Stefan
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorGergeleit, Martin
dc.contributor.editorMartin, Ludger
dc.date.accessioned2024-10-21T18:24:18Z
dc.date.available2024-10-21T18:24:18Z
dc.date.issued2024
dc.description.abstractThis paper introduces a novel algorithm specifically designed to address the unique complexities of icon-based tables in digital documents. Our algorithm leverages a combination of computer vision techniques to accurately detect table grids, identify symbols, and insert them into their relative positions.en
dc.identifier.doi10.18420/inf2024_173
dc.identifier.isbn978-3-88579-746-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45151
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-352
dc.subjecttable extraction
dc.subjecteducation data
dc.subjecthigher education
dc.titleAutomated Extraction of Icon-based Tablesen
dc.typeText/Conference Paper
gi.citation.endPage2005
gi.citation.publisherPlaceBonn
gi.citation.startPage2003
gi.conference.date24.-26. September 2024
gi.conference.locationWiesbaden
gi.conference.sessiontitleDigitalization and AI for and in Education and Educational Research (DAI-EaR'24)

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