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Underground Archeological Structures Detection

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    SYSNO ASEP0546213
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleUnderground Archeological Structures Detection
    Author(s) Moudrá, A. (CZ)
    Haindl, Michal (UTIA-B) RID, ORCID
    Number of authors2
    Article number56
    Source TitleAdvances in Computational Collective Intelligence. - Cham : Springer International Publishing, 2021 / Wojtkiewicz Krystian ; Treur Jan ; Pimenidis Elias ; Maleszka Marcin - ISSN 1865-0929 - ISBN 978-3-030-88113-9
    Pagess. 690-702
    Number of pages13 s.
    Publication formPrint - P
    ActionInternational Conference on Computational Collective Intelligence 2021 /13./
    Event date29.09.2021 - 01.10.2021
    VEvent locationKallithea, Rhodes
    CountryGR - Greece
    Event typeWRD
    Languageeng - English
    CountryCH - Switzerland
    KeywordsRemote sensing archeology ; underground heritage site recognition ; aerial image-based automated site detection
    Subject RIVBD - Theory of Information
    OECD categoryCommunication engineering and systems
    R&D ProjectsGA19-12340S GA ČR - Czech Science Foundation (CSF)
    Institutional supportUTIA-B - RVO:67985556
    DOI https://doi.org/10.1007/978-3-030-88113-9_56
    AnnotationThis paper introduces and compares three approaches for automatic archaeological heritage site detection hidden under soil cover from public aerial images. The methods use low quality public aerial RGB spectral data restricted by the land-use map to agricultural regions in the vegetation season to detect underground structure influencing plants growing on the surface soil layer.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2022
    Electronic addresshttp://library.utia.cas.cz/separaty/2021/RO/haindl-0546213.pdf
Number of the records: 1  

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