Automated Extraction of Icon-based Tables

This 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.

Thome, Boris; Hertweck, Friederike; Jonas, Lukas; Yasar, Serife; Conrad, Stefan (2024): Automated Extraction of Icon-based Tables. INFORMATIK 2024. DOI: 10.18420/inf2024_173. Bonn: Gesellschaft für Informatik e.V.. ISSN: 2944-7682. PISSN: 1617-5468. EISSN: 2944-7682. ISBN: 978-3-88579-746-3. pp. 2003-2005. Digitalization and AI for and in Education and Educational Research (DAI-EaR'24). Wiesbaden. 24.-26. September 2024

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table extraction , education data , higher education

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10.18420/inf2024_173

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P352 - INFORMATIK 2024 - Lock in or log out? Wie digitale Souveränität gelingt

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Automated Extraction of Icon-based Tables

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