Situation Awareness for UAVs using Deep Learning techniques

抄録

Unmaned Aerial Vehicle (UAV) missions or applications, both manually controlled or autonomous, require the operator to be aware of what is happening around the UAV. In this paper we introduce an approach dividing this visual situation awareness problem into different levels, which we first try to solve separately using different deep learning techniques and later integrate into a single model using Multi-Task Learning techniques, with the aim of deploying it on an embedded system mounted on the UAV itself for running in real-time.