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1 Ergebnisse
1
Fine-grained Spatiotemporal Features-Based for Anomaly Dete..:
, In:
2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)
,
Yang, Xikang
;
Wang, Juan
;
Zhou, Biyu
... - p. 847-856 , 2022
Link:
https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys57..
RT T1
2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)
: T1
Fine-grained Spatiotemporal Features-Based for Anomaly Detection in Microservice Systems
UL https://suche.suub.uni-bremen.de/peid=ieee-10074842&Exemplar=1&LAN=DE A1 Yang, Xikang A1 Wang, Juan A1 Zhou, Biyu A1 Wang, Wang A1 Liu, Wantao A1 Dong, Yangchen YR 2022 K1 Measurement K1 Network topology K1 Neural networks K1 Microservice architectures K1 Maintenance engineering K1 Feature extraction K1 Spatiotemporal phenomena K1 Anomaly Detection K1 Graph Neural Networks K1 Microservice Systems SP 847 OP 856 LK http://dx.doi.org/https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys57074.2022.00138 DO https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys57074.2022.00138 SF ELIB - SuUB Bremen
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