When Wafer Failure Pattern Classification Meets Few-shot Learning and Self-Supervised Learning-Reference-Cited by-同舟云学术

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When Wafer Failure Pattern Classification Meets Few-shot Learning and Self-Supervised Learning

Published:2021-11-01 Issue: Volume: Page:
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Container-title:2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)
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Author:

Geng Hao,Yang Fan,Zeng Xuan,Yu Bei

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9643423/9643432/09643518.pdf?arnumber=9643518

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A self-supervised learning framework based on masked autoencoder for complex wafer bin map classification;Expert Systems with Applications;2024-09

2. Generalized zero-shot learning for classifying unseen wafer map patterns;Engineering Applications of Artificial Intelligence;2024-07

3. An unknown wafer surface defect detection approach based on Incremental Learning for reliability analysis;Reliability Engineering & System Safety;2024-04

4. WaSSaBi: Wafer Selection With Self-Supervised Representations and Brain-Inspired Active Learning;IEEE Transactions on Circuits and Systems I: Regular Papers;2024-04

5. PaLM: Point Cloud and Large Pre-trained Model Catch Mixed-type Wafer Defect Pattern Recognition;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

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