The Classification of Wafer Defects: An Evaluation of Different Feature-Based ResNet Transfer Learning Models with Support Vector Machine-Reference-Cited by-同舟云学术

The Classification of Wafer Defects: An Evaluation of Different Feature-Based ResNet Transfer Learning Models with Support Vector Machine

Published:2023 Issue: Volume: Page:277-283
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Xuen Lim Shi,Mohd Khairuddin Ismail,Mohd Razman Mohd Azraai,Mat Jizat Jessnor Arif,Yuen Edmund,Yap Eng Hwa,Tan Andrew Huey Ping,Abdul Majeed Anwar P. P.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-8703-8_23

Reference11 articles.

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3. Kumar JLM, Rashid M, Musa RM, Razman MAM, Sulaiman N, Jailani R, Abdul Majeed APP (2021) The classification of EEG-based wink signals: a CWT-Transfer Learning pipeline. ICT Express. https://doi.org/10.1016/j.icte.2021.01.004

4. Mahendra Kumar JL, Rashid M, Muazu Musa R, Mohd Razman MA, Sulaiman N, Jailani R, Abdul Majeed PPA (2021) The classification of EEG-based winking signals: a transfer learning and random forest pipeline. PeerJ 9:e11182. https://doi.org/10.7717/peerj.11182

5. Abdullah MA, Ibrahim MAR, Shapiee, Bin MNA, Mohd Razman MA, Musa RM, Abdul Majeed APP (2020) The classification of skateboarding trick manoeuvres through the integration of IMU and machine learning. In: Lecture notes in mechanical engineering. Springer, pp 67–74. https://doi.org/10.1007/978-981-13-9539-0_7