Detection defect in printed circuit boards using unsupervised feature extraction upon transfer learning

• Main Authors: Volkau, Ihar, Abdul Mujeeb, Dai, Wenting, Erdt, Marius, Sourin, Alexei
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering; Automated Manufacturing Systems; Cyber Manufacturing
• Online Access: https://hdl.handle.net/10356/137974
• Institution: Nanyang Technological University

Automatic optical inspection for manufacturing traditionally was based on computer vision. However, there are emerging attempts to do it using deep learning approach. Deep convolutional neural network allows to learn semantic image features which could be used for defect detection in products. In co...