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RF-Q: Unsupervised Signal Quality Assessment for Robust RF-..:
, In:
2023 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
,
Xie, Zongxing
;
Nederlander, Ava
;
Park, Isac
. - p. 158-162 , 2023
Link:
https://doi.org/10.1145/3580252.3586988
RT T1
2023 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
: T1
RF-Q: Unsupervised Signal Quality Assessment for Robust RF-based Respiration Monitoring
UL https://suche.suub.uni-bremen.de/peid=ieee-10183741&Exemplar=1&LAN=DE A1 Xie, Zongxing A1 Nederlander, Ava A1 Park, Isac A1 Ye, Fan YR 2023 SN 2832-2975 K1 Radio frequency K1 RF signals K1 Neural networks K1 Estimation K1 Distortion K1 Robustness K1 Quality assessment K1 RF sensing K1 signal quality assessment K1 vital signs monitoring K1 signal reconstruction K1 unsupervised learning K1 autoencoder (AE) SP 158 OP 162 LK http://dx.doi.org/https://doi.org/10.1145/3580252.3586988 DO https://doi.org/10.1145/3580252.3586988 SF ELIB - SuUB Bremen
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