Significance of activation functions in developing an online classifier for semiconductor defect detection

作者：

Highlights：

• Machine learning guided online defect detection in advanced semiconductor devices.

• Development of Leaky-ReLU-based novel evolving neuro-fuzzy system.

• Evaluation of proposed system in single-pass mode.

• Evaluation of proposed system under the prequential test-then-train protocol.

摘要

•Machine learning guided online defect detection in advanced semiconductor devices.•Development of Leaky-ReLU-based novel evolving neuro-fuzzy system.•Evaluation of proposed system in single-pass mode.•Evaluation of proposed system under the prequential test-then-train protocol.

论文关键词：Leaky ReLU,Online learning,Defect detection,Prequential,Semiconductors

论文评审过程：Received 24 September 2021, Revised 9 April 2022, Accepted 12 April 2022, Available online 21 April 2022, Version of Record 7 May 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.108818