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cs.LG2022
A Novel Self-Supervised Learning-Based Anomaly Node Detection Method Based on an Autoencoder in Wireless Sensor Networks
Miao Ye, Qinghao Zhang, Xingsi Xue +3
Due to the issue that existing wireless sensor network (WSN)-based anomaly detection methods only consider and analyze temporal features, in this paper, a self-supervised learning-…
cs.LG2022
A Novel Anomaly Detection Method for Multimodal WSN Data Flow via a Dynamic Graph Neural Network
Qinghao Zhang, Miao Ye, Hongbing Qiu +2
Anomaly detection is widely used to distinguish system anomalies by analyzing the temporal and spatial features of wireless sensor network (WSN) data streams; it is one of critical…