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Loop closure detection is an important component of visual simultaneous localization and mapping (SLAM). However, most existing loop closure detection methods are vulnerable to complex environments and use limited information from images. As higher-level image information and multi-information fusion can improve the robustness of place recognition, a semantic–visual–geometric information-based loop closure detection algorithm (SVG-Loop) is proposed in this paper. In detail, to reduce thedoi:10.3390/rs13173520 doaj:23de87f2c2584ad0863033039e1af32c fatcat:qcvcljaka5c3flrn6qrzfj32je