Abstract
A semi-automatic tool for fast and accurate annotation of endoscopic videos utilizing trained object detection models is presented. A novel workflow is implemented and the preliminary results suggest that the annotation process is nearly twice as fast with our novel tool compared to the current state of the art.
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