COVID-19 detection exploiting self-supervised learning representations of respiratory sounds

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Metadaten
Author:Adria Mallol-Ragolta, Shuo Liu, Björn SchullerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1156397
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/115639
ISBN:978-1-6654-8791-7OPAC
Parent Title (English):2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 27-30 September 2022, Ioannina, Greece
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Dimitris I. Fotiadis, Constantinos S. Pattichis, May D. Wang
Type:Conference Proceeding
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2024/10/02
First Page:1
Last Page:4
DOI:https://doi.org/10.1109/bhi56158.2022.9926967
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 3 - Gesundheit und Wohlergehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht