Class-Driven Graph Attention Network for Multi-Label Time Series Classification in Mobile Health Digital Twins
Download
Full text for this resource is not available from the Research Repository.
Export
Sun, Le ORCID: 0000-0002-4221-0327, Li, Chenyang, Liu, Bo ORCID: 0000-0002-5279-5322 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2023) Class-Driven Graph Attention Network for Multi-Label Time Series Classification in Mobile Health Digital Twins. IEEE Journal on Selected Areas in Communications, 41 (10). pp. 3267-3278. ISSN 0733-8716
Dimensions Badge
Altmetric Badge
Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/48056 |
DOI | 10.1109/JSAC.2023.3310064 |
Official URL | https://ieeexplore.ieee.org/document/10234411 |
Subjects | Current > FOR (2020) Classification > 4606 Distributed computing and systems software Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
Keywords | Digital Twins for Mobile Networks; mHealth; multi-class classification; feature extraction; C-DGAM |
Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)