Tile Defect Detection

Automated manual tile inspection on a scorching production line using a Siamese U-Net++ segmentation model achieving 0.98 Dice coefficient and 90% F1 score. Solved the challenge of complex tile patterns mimicking defects through data augmentation and novel label modification techniques.