0536614 - ÚI 2021 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
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]
Grant CEP: GA ČR(CZ) GA18-18080S
Institucionální podpora: RVO:67985807
Klíčová slova: Active Learning * Anomaly detection * LSTM-Autoencoder * Time series
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Web výsledku:
http://ceur-ws.org/Vol-2660/ialatecml_shortpaper1.pdf
Trvalý link: http://hdl.handle.net/11104/0314366