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A deep-learning pipeline for enhancing the detection of faint moving objects in optical space situational awareness (SSA) imagery through automated star removal and background reconstruction is presented, thereby providing an effective data-driven preprocessing strategy for faint moving-object detection in optical SSA scenarios.
