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

• المؤلفون الرئيسيون: Volkau, Ihar, Abdul Mujeeb, Dai, Wenting, Erdt, Marius, Sourin, Alexei
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Automated Manufacturing Systems; Cyber Manufacturing
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/137974

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...