Industrial Vision Systems and Defect Detection

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.

How has Industrial Vision Systems and Defect Detection's publication output changed over time?

Output grew0% over the shown period — from 1 works in 2012 to 1 in 2023.

What are the most-cited papers on Industrial Vision Systems and Defect Detection?

Where is Industrial Vision Systems and Defect Detection research published, and who funds it?

How much of the research on Industrial Vision Systems and Defect Detection is open access?