The Classification of Wafer Defects: A Support Vector Machine with Different DenseNet Transfer Learning Models Evaluation

• Main Authors: Ismail, Mohd Khairuddin, Lim, Shi Xuen, Mohd Azraai, Mohd Razman, Jessnor Arif, Mat Jizat, Yuen, Edmund, Jiang, Haochuan, Yap, Eng Hwa, Anwar, P. P. Abdul Majeed
• Format: Conference or Workshop Item
• Language: English
• Published: Springer Nature 2023
• Subjects: TJ Mechanical engineering and machinery; TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/37269/1/The%20Classification%20of%20Wafer%20Defects%20A%20Support%20Vector%20Machine%20with%20Different%20DenseNet%20Transfer%20Learning%20Models%20Evaluation%20%281%29.pdf; http://umpir.ump.edu.my/id/eprint/37269/; https://doi.org/10.1007/978-3-031-26889-2_27

Wafer defect detection is a non-trivial issue in the semiconductor industry. Conventional means of defect detection is often labor-intensive based that is prone to error owing to a myriad of issue. Hence, there is push toward automatic defect detection in the industry. This work shall investigate th...