Performance monitoring of deep learning vision systems during deployment

Abstract

This thesis investigates how to monitor the performance of deep learning vision systems in mobile robots. It conducts state-of-the-art research to validate the real-time performance of mobile robots such as self-driving cars. This research is significant for deploying visual sensor-dependent autonomous vehicles in our daily lives. This knowledge will alert a mobile robot about its performance degradation to take preventive measures to reduce the risk of hazardous consequences for the robot, its surroundings and any person involved