Li-Jun Cui

Zero-Shot Wireless Sensor Anomaly Detection via Global-Local Temporal Representation Learning

Zero-shot anomaly detection (ZSAD) in wireless sensor networks (WSNs) is essential for mission-critical applications such as smart homes and assisted living. However, existing methods rely heavily on large annotated datasets, limiting their ability to generalize to unseen anomaly types and increasing deployment costs....