Oleg Kovtun
Deep learning, a powerful and widely effective subset of machine learning, offers a promising foundation for developing an automatic, parameter-free analysis pipelines that replace conventional, multistep workflows for single quantum dot tracking. This chapter provides detailed protocols for installing and implementing open-source, state-of-the-art deep learning tools to detect individual quantum dots in time-lapse image series and reconstruct their trajectories. Additionally, it includes practical guidelines for troubleshooting common errors encountered when deploying these tools for single quantum dot tracking.