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1 Ergebnisse
1
Wrist-worn accelerometer based fall detection for embedded ..:
, In:
Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments
,
Kraft, Dimitri
;
Srinivasan, Karthik
;
Bieber, Gerald
- p. 1-10 , 2020
Link:
https://dl.acm.org/doi/10.1145/3389189.3397983
RT T1 <cTitle>Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments</cTitle>: T1 <Title>Wrist-worn accelerometer based fall detection for embedded systems and IoT devices using deep learning algorithms</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3397983&Exemplar=1&LAN=DE A1 Kraft, Dimitri A1 Srinivasan, Karthik A1 Bieber, Gerald PB ACM YR 2020 K1 IoT devices K1 accelerometer K1 datasets K1 deep learning K1 edge computing K1 fall detection K1 neural networks K1 Computing methodologies K1 Machine learning K1 Machine learning algorithms K1 Human-centered computing K1 Ubiquitous and mobile computing K1 Empirical studies in ubiquitous and mobile computing K1 Cross-validation SP 1 OP 10 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3389189.3397983 DO https://dl.acm.org/doi/10.1145/3389189.3397983 SF ELIB - SuUB Bremen
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