Nowadays drone usage is increasing due to their technological advancements, versatility, and broad applicability for a wide range of tasks. Improved capabilities in the drone sector and tech miniaturization such as the development of smaller and more powerful embedded systems allow AI to be integrated and efficiently run aboard them. Standard-size drones can be equipped with powerful Graphics Processing Units (GPUs) that allow the use of complex neural networks to solve perception tasks. However, nano-drones, with their extremely small dimensions and power envelope, have major limitations in terms of supported computational capabilities. Thus, there is a need to develop more optimized solutions to enable onboard AI, preserving the real-time response of the perception system while maximizing the performance of the considered task.