Challenge

The task at hand is to automatically verify the quality of metallic grids by scanning the surface for various defects.

Solution

Given some example images of the corresponding grid structure of good quality we trained an anomaly detection model for detecting patterns on the surface which deviate from the normal data.

Impact

The resulting model was able to precisely localise various kinds of defects. The training requires only normal data without the need of manual annotation.