A Dataset for Semantic Segmentation in the Presence of Unknowns
Before deployment in the real-world deep neural networks require thorough evaluation of how they handle both knowns, inputs represented in the training […]
Towards Securing IIoT: An Innovative Privacy-Preserving Anomaly Detector Based on Federated Learning
In the light of the growing connectivity and sensitivity of industrial data, cyberattacks and data breaches are becoming more common in the […]
Detection and Classification of Anomalies in WSN-enabled Cyber-physical Systems
Detection and classification of anomalies in industrial applications has long been a focus of interest in the research community. The integration of […]