Synthetic data generation framework for quality control automation in gravure printing

AI Digest - ArXiv AI

Synthetic data generation framework for quality control automation in gravure printing

Quality control in printing, particularly in rotogravure printing, still depends on slow, costly, and subjective manual inspection. Automated surface defect detection is critical for maintaining high-quality standards in rotogravure printing. Deep learning models give prospects for automation. However, training robust deep learning models, such as YOLO or Vision Transformers, is heavily hindered by the extreme scarcity of real-world industrial defects images. To overcome this limitation, this pa

Source: ArXiv AI