Learning multimodal representations for drowsiness detection

Download full text files

  • 91570.pdfeng
    (1000KB)

    Postprint. © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Export metadata

Statistics

Number of document requests

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Kun Qian, Tomoya Koike, Toru Nakamura, Björn W. SchullerORCiDGND, Yoshiharu Yamamoto
URN:urn:nbn:de:bvb:384-opus4-915702
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/91570
ISSN:1524-9050OPAC
ISSN:1558-0016OPAC
Parent Title (English):IEEE Transactions on Intelligent Transportation Systems
Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Place of publication:New York, NY
Type:Article
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2022/01/26
Tag:Computer Science Applications; Mechanical Engineering; Automotive Engineering
Volume:23
Issue:8
First Page:11539
Last Page:11548
DOI:https://doi.org/10.1109/tits.2021.3105326
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
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht

OPUS4 Logo