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Active Learning for LSTM-autoencoder-based Anomaly Detection in Electrocardiogram Readings

  1. 1.
    0536614 - ÚI 2021 RIV DE eng C - Conference Paper (international conference)
    Šabata, T. - Holeňa, Martin
    Active Learning for LSTM-autoencoder-based Anomaly Detection in Electrocardiogram Readings.
    Proceedings of the Workshop on Interactive Adaptive Learning. Aachen: Technical University & CreateSpace Independent Publishing, 2020 - (Kottke, D.; Krempl, G.; Lemaire, V.; Holzinger, A.; Calma, A.), s. 72-77. CEUR Workshop Proceedings, 2660. ISSN 1613-0073.
    [IAL 2020: International Workshop on Interactive Adaptive Learning /4./. Virtual Ghent (BE), 14.09.2020-14.09.2020]
    R&D Projects: GA ČR(CZ) GA18-18080S
    Institutional support: RVO:67985807
    Keywords : Active Learning * Anomaly detection * LSTM-Autoencoder * Time series
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    http://ceur-ws.org/Vol-2660/ialatecml_shortpaper1.pdf

    Permanent Link: http://hdl.handle.net/11104/0314366
    FileDownloadSizeCommentaryVersionAccess
    0536614-aw.pdf0527.4 KBvolně onlinePublisher’s postprintopen-access
     
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