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1 Ergebnisse
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What Actually Works for Activity Recognition in Scenarios w..:
Stefan Kalabakov
;
Simon Stankoski
;
Ivana Kiprijanovska
...
https://www.mdpi.com/1424-8220/22/10/3613. , 2022
Link:
https://doi.org/10.3390/s22103613
RT Journal T1
What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:0df6b9a029c643edacf4d5f67b639d1c&Exemplar=1&LAN=DE A1 Stefan Kalabakov A1 Simon Stankoski A1 Ivana Kiprijanovska A1 Andrejaana Andova A1 Nina Reščič A1 Vito Janko A1 Martin Gjoreski A1 Matjaž Gams A1 Mitja Luštrek PB MDPI AG YR 2022 K1 activity recognition K1 machine learning K1 competition K1 smartphone K1 semi-supervised learning K1 Hidden Markov models K1 Chemical technology K1 TP1-1185 JF https://www.mdpi.com/1424-8220/22/10/3613 LK http://dx.doi.org/https://doi.org/10.3390/s22103613 DO https://doi.org/10.3390/s22103613 SF ELIB - SuUB Bremen
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