首页|Findings from Central China Normal University Reveals New Findings on Intelligent Systems (An Enhanced Abnormal Information Expression Spatiotemporal Model for Anomaly Detection In Multivariate Time-series)
Findings from Central China Normal University Reveals New Findings on Intelligent Systems (An Enhanced Abnormal Information Expression Spatiotemporal Model for Anomaly Detection In Multivariate Time-series)
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NETL
NSTL
Springer Nature
Investigators publish new report on Machine Learning - Intelligent Systems. According to news reporting originating from Wuhan, People's Republic of China, by NewsRx correspondents, research stated, “The detection of anomalies in high-dimensional time-series has always played a crucial role in the domain of system security. Recently, with rapid advancements in transformer model and graph neural network (GNN) technologies, spatiotemporal modeling approaches for anomaly detection tasks have been greatly improved.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), Centre for Research in Cyber Security, Singapore University of Technology and Design.
WuhanPeople’s Republic of ChinaAsiaIntelligent SystemsMachine LearningCybersecurityCentral China Normal University
NETL
NSTL
Springer Nature
