Addressing these gaps, this work proposes a quantum-inspired federated learning framework for anomaly detection that guarantees data privacy in a distributed environment.

Anomaly detection (AD) of gearboxes is essential for ensuring the operational safety and reliability of the loader. However, identifying anomalies in non-stationary signals remains challenging as ...

Discussion: The dual autoencoder model, which integrates reconstruction errors from both healthy and glaucomatous training data, demonstrated superior diagnostic accuracy compared to the single ...

Anomaly detection on attributed networks aims at finding nodes whose patterns deviate significantly from the majority of reference nodes, which is pervasive in many applications such as network ...