Review: Application of Convolutional Neural Network in Defect Detection of 3C Products

Abstract

Based on the rapid development of semiconductors, integrated circuits and the Internet. 3C products such as computers, tablets, mobile phones and smart TVs have become an indispensable part of people’s lives. With the prosperity and development of the 3C product market, the demand for the quality of display panels and related detection technologies are increasing. As the iconic network of deep learning, has been extensively studied in the field of image recognition and defect detection. Based on the development of CNN, this article summarizes the defect detection method of 3C products by CNN with different depths. First, we reviewed the origin of CNN and its structural components, then introduced the upgrade and improvement of important components, and finally introduced and compared the applications of CNN with different depths in defect detection. Through the comparison and summary of the effect of defect detection, we analyze the opportunities and challenges of different CNN frameworks, and exhibit the strategies for different application scenarios.

Keywords

• 3C products
• defect detecting
• neural network
• convolution network