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1 Ergebnisse
1
A Deep Learning Approach for Real-Time Application-Level An..:
, In:
2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)
,
Raeiszadeh, Mahsa
;
Saleem, Ahsan
;
Ebrahimzadeh, Amin
... - p. 449-454 , 2023
Link:
https://doi.org/10.1109/CCNC51644.2023.10060584
RT T1
2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)
: T1
A Deep Learning Approach for Real-Time Application-Level Anomaly Detection in IoT Data Streaming
UL https://suche.suub.uni-bremen.de/peid=ieee-10060584&Exemplar=1&LAN=DE A1 Raeiszadeh, Mahsa A1 Saleem, Ahsan A1 Ebrahimzadeh, Amin A1 Glitho, Roch H. A1 Eker, Johan A1 Mini, Raquel A. F. YR 2023 SN 2331-9860 K1 Measurement K1 Deep learning K1 Predictive models K1 Performance gain K1 Real-time systems K1 Data models K1 Fourth Industrial Revolution K1 Anomaly Detection K1 Deep Learning K1 Real-time Analytics K1 LSTM K1 Streaming Data SP 449 OP 454 LK http://dx.doi.org/https://doi.org/10.1109/CCNC51644.2023.10060584 DO https://doi.org/10.1109/CCNC51644.2023.10060584 SF ELIB - SuUB Bremen
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