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\label{sec:contributions}  The first contribution of this thesis is a machine learning-based  indoor localization system that is able to run runs  in real-time on board of an MAV, paving the way to a fully autonomous system. In contrast to  existing \emph{active} approaches, the proposed \emph{passive}  approach only uses a single, monocular, downward-looking camera. Since