A pointer-based, in-situ annotation system captures physical trajectories on inspected objects and converts them into standard ML training annotations, with preliminary tests showing deviations below about 1.6 mm.
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Physical Annotation for Automated Optical Inspection: A Concept for In-Situ, Pointer-Based Training Data Generation
A pointer-based, in-situ annotation system captures physical trajectories on inspected objects and converts them into standard ML training annotations, with preliminary tests showing deviations below about 1.6 mm.