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digital twin

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GeoAIPoint Cloud Segmentation

Separate candidate ground from elevated LiDAR returns with cloth simulation. A practical non-neural baseline for terrain preparation.

GeoAIChange Detection

Compare aligned point clouds from two dates to learn spatial change classes, with clear separation between survey differences and real change.

GeoAIPoint Cloud Segmentation

Explore semantic classes and separate object instances in 3D, extending point-wise labels toward individual survey objects.

GeoAITime-Series Forecasting

Forecast sensor histories with uncertainty intervals and optional covariates. Evaluate each deployment against local temporal baselines.

GeoAIAnomaly & Defect Detection

Learn normal visual appearance and flag unusual image regions for review. Build a task-specific memory bank before inspecting new assets.

GeoAI3D Reconstruction

Explore learned image matching and point-map reconstruction from overlapping photos, with explicit scale, georeferencing and licensing checks.

GeoAIPoint Cloud Registration

Align overlapping point clouds with learned geometric correspondences, then review the transformation before updating a shared 3D scene.

GeoAI3D Object Detection

Locate road users in LiDAR with oriented 3D boxes. Explore the official OpenPCDet KITTI baseline and the steps needed for a new survey.