As the number of in-orbit satellites increases, the need for precise pose estimation becomes increasingly critical. Recently the EU funded EROSS, a project with the purpose of providing a new range of services for in orbit satellites with consequent analysis for satellite design and life-cycle management. This initiative aims to enhance the availability of cost-effective and secure orbital services by assessing and validating the essential technological components of the Servicer spacecraft. The incorporation of robotic space technologies working on this project will lead to greater autonomy and safety in executing these services in space, requiring reduced ground-based supervision. This master's thesis presents an innovative approach to pose estimation using deep learning and computer vision techniques.