Detection of Monocrystalline Silicon Wafer Defects Using Deep Transfer Learning

• Main Authors: Adriana, Ganum, Dayang Nurfatimah, Awang Iskandar, Phei Chin, Lim, Ahmad Hadinata, Fauzi
• Format: Article
• Language: English
• Published: Journal of Telecommunications and Information Technology 2022
• Subjects: T Technology (General)
• Online Access: http://ir.unimas.my/id/eprint/38468/1/34.pdf; http://ir.unimas.my/id/eprint/38468/; https://www.itl.waw.pl/pl/publikacje/jtit; https://doi.org/10.26636/jtit.2022.156321

Defect detection is an important step in industrial production of monocrystalline silicon. Through the study of deep learning, this work proposes a framework for classifying monocrystalline silicon wafer defects using deep transfer learning (DTL). An existing pre-trained deep learning model was used...