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Lightweight semantic segmentation for construction progress monitoring using 3D point clouds
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DOI：10.1016/j.autcon.2026.106765.png)
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Abstract
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• Lightweight L-PointNet++ model for fast 3D point cloud segmentation • Dual-stage training strategy for effective edge and corner segmentation • Dynamo-based BIM reconstruction pipeline enabling rapid progress monitoring • High accuracy (mIoU >0.93) on real construction data • Enhanced project management with schedule-deviation detection
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