Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection

This paper proposes MODIAD, a novel framework for Multimodal Online Distributed Industrial Anomaly Detection, addressing limitations of existing methods in real-world industrial environments. It aims to leverage edge intelligence for distributed model training in industrial systems.