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1 Ergebnisse
1
FieldHAR: A Fully Integrated End-to-End RTL Framework for H..:
, In:
2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP)
,
Liu, Mengxi
;
Zhou, Bo
;
Zhao, Zimin
... - p. 110-118 , 2023
Link:
https://doi.org/10.1109/ASAP57973.2023.00029
RT T1 <cTitle>2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP)</cTitle>: T1 <Title>FieldHAR: A Fully Integrated End-to-End RTL Framework for Human Activity Recognition with Neural Networks from Heterogeneous Sensors</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10265732&Exemplar=1&LAN=DE A1 Liu, Mengxi A1 Zhou, Bo A1 Zhao, Zimin A1 Hong, Hyeonseok A1 Kim, Hyun A1 Suh, Sungho A1 Rey, Vitor Fortes A1 Lukowicz, Paul YR 2023 SN 2160-052X K1 Runtime K1 Data acquisition K1 Transforms K1 Parallel processing K1 Throughput K1 Sensors K1 Human activity recognition K1 FPGA K1 Sensor Fusion K1 Human Activity Recognition K1 Neural Networks SP 110 OP 118 LK http://dx.doi.org/https://doi.org/10.1109/ASAP57973.2023.00029 DO https://doi.org/10.1109/ASAP57973.2023.00029 SF ELIB - SuUB Bremen
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