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Short: RF-Q: Unsupervised Signal Quality Assessment for Rob..:
, In:
Proceedings of the 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies
,
Xie, Zongxing
;
Nederlander, Ava
;
Park, Isac
. - p. 158-162 , 2023
Link:
https://dl.acm.org/doi/10.1145/3580252.3586988
RT T1 <cTitle>Proceedings of the 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies</cTitle>: T1 <Title>Short: RF-Q: Unsupervised Signal Quality Assessment for Robust RF-based Respiration Monitoring</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3586988&Exemplar=1&LAN=DE A1 Xie, Zongxing A1 Nederlander, Ava A1 Park, Isac A1 Ye, Fan PB ACM YR 2023 K1 RF sensing K1 signal quality assessment K1 vital signs monitoring K1 signal reconstruction K1 unsupervised learning K1 autoencoder (AE) K1 Applied computing K1 Life and medical sciences K1 Health informatics K1 Bioinformatics K1 Health care information systems K1 Human-centered computing K1 Ubiquitous and mobile computing K1 Empirical studies in ubiquitous and mobile computing SP 158 OP 162 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580252.3586988 DO https://dl.acm.org/doi/10.1145/3580252.3586988 SF ELIB - SuUB Bremen
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