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1 Ergebnisse
1
Deep Convolutional Autoencoder for Assessment of Drive-Cycl..:
, In:
2022 IEEE Symposium Series on Computational Intelligence (SSCI)
,
Geglio, Anthony
;
Hedayati, Eisa
;
Tascillo, Mark
... - p. 743-749 , 2022
Link:
https://doi.org/10.1109/SSCI51031.2022.10022233
RT T1 <cTitle>2022 IEEE Symposium Series on Computational Intelligence (SSCI)</cTitle>: T1 <Title>Deep Convolutional Autoencoder for Assessment of Drive-Cycle Anomalies in Connected Vehicle Sensor Data</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10022233&Exemplar=1&LAN=DE A1 Geglio, Anthony A1 Hedayati, Eisa A1 Tascillo, Mark A1 Anderson, Dyche A1 Barker, Jonathan A1 Havens, Timothy C. YR 2022 K1 Deep learning K1 Convolution K1 Fault detection K1 Time series analysis K1 Mechanical power transmission K1 Task analysis K1 Intelligent sensors K1 Anomaly detection K1 vehicle sensor analysis K1 automotive fault detection K1 multivariate time series SP 743 OP 749 LK http://dx.doi.org/https://doi.org/10.1109/SSCI51031.2022.10022233 DO https://doi.org/10.1109/SSCI51031.2022.10022233 SF ELIB - SuUB Bremen
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