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1
Investigating the Effect of Orientation Variability in Deep..:
, In:
Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing
,
Khaked, Azhar Ali
;
Oishi, Nobuyuki
;
Roggen, Daniel
. - p. 480-485 , 2023
Link:
https://dl.acm.org/doi/10.1145/3594739.3610742
RT T1 <cTitle>Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing</cTitle>: T1 <Title>Investigating the Effect of Orientation Variability in Deep Learning-based Human Activity Recognition</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3610742&Exemplar=1&LAN=DE A1 Khaked, Azhar Ali A1 Oishi, Nobuyuki A1 Roggen, Daniel A1 Lago, Paula PB ACM YR 2023 K1 deep learning K1 domain shift K1 human activity recognition K1 wearable sensors K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning K1 Supervised learning by classification K1 Human-centered computing K1 Ubiquitous and mobile computing K1 Ubiquitous and mobile computing theory, concepts and paradigms K1 Ubiquitous computing SP 480 OP 485 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3594739.3610742 DO https://dl.acm.org/doi/10.1145/3594739.3610742 SF ELIB - SuUB Bremen
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