A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles

Figure 1

Aerostack architecture, consisting of a layered structure, corresponding to the different abstraction levels in an unmanned aerial robotic system. The architecture has been applied here to systematically classify deep learning-based algorithms available in the state of the art which have been deployed for applications with Unmanned Aerial Vehicles.