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Digital twin : a machine learning approach to predict in..:
, In:
Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
,
Scheuermann, Constantin
;
Binderberger, Thomas
;
von Frankenberg, Nadine
. - p. 657-664 , 2020
Link:
https://dl.acm.org/doi/10.1145/3410530.3414316
RT T1 <cTitle>Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers</cTitle>: T1 <Title>Digital twin : a machine learning approach to predict individual stress levels in extreme environments</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3414316&Exemplar=1&LAN=DE A1 Scheuermann, Constantin A1 Binderberger, Thomas A1 von Frankenberg, Nadine A1 Werner, Andreas PB ACM YR 2020 SP 657 OP 664 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3410530.3414316 DO https://dl.acm.org/doi/10.1145/3410530.3414316 SF ELIB - SuUB Bremen
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