This cluster of papers focuses on the application of machine vision, texture analysis, and deep learning techniques for the automated detection and classification of fabric defects in industrial settings, particularly in semiconductor manufacturing. The research covers various methods such as Gabor filters, wafer map defect classification, and virtual metrology to enhance the accuracy and efficiency of fabric defect detection systems.