arXiv cs.CV
· Papers
A Masked Autoencoder Approach to Unsupervised Steel Surface Defect Recognition
arXiv:2607.13178v1 Announce Type: new Abstract: Automated visual inspection of steel surface defects is a recurring quality control task in which labeled defect data is scarce and costly to obtain, while unlabeled surface images are abundant, which motivates self supervised methods that learn useful representations wit