Supervised Vision-based Anomaly Detection

In the following paper associated with a demonstration, we describe an in- house designed, developed and deployed versatile anomaly detection model called SCNet. The model is based on state-of-the-art deep learning techniques, and is targeted for deployment within inspection and quality assessment systems, including edge deployment for battery-challenged vast outdoor scenarios. We also provide the details of the corresponding edge demonstration.