Wafer Defect Pattern Labeling and Recognition Using Semi-Supervised Learning-Reference-Cited by-同舟云学术

Wafer Defect Pattern Labeling and Recognition Using Semi-Supervised Learning

Published:2022-05 Issue:2 Volume:35 Page:291-299
ISSN:0894-6507
Container-title:IEEE Transactions on Semiconductor Manufacturing
language:
Short-container-title:IEEE Trans. Semicond. Manufact.

Author:

Li Katherine Shu-Min¹^ORCID,Jiang Xu-Hao¹,Chen Leon Li-Yang¹,Wang Sying-Jyan²^ORCID,Huang Andrew Yi-Ann³,Chen Jwu E.⁴,Liang Hsing-Chung⁵^ORCID,Hsu Chun-Lung⁶

Affiliation:

1. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan

2. Department of Computer Science and Engineering, National Chung Hsing University, Taichung, Taiwan

3. Department of Wafer Test, NXP Semiconductors Taiwan Ltd., Kaohsiung, Taiwan

4. Department of Electrical Engineering, National Central University, Chungli, Taiwan

5. Department of Electrons Engineering, Chung Yuan Christian University, Chungli, Taiwan

6. Division for Design Automation Technology, Information and Communication Research Laboratories, Industrial Technology Research Institute, Hsinchu, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

http://xplorestaging.ieee.org/ielx7/66/9768876/09733906.pdf?arnumber=9733906

Reference25 articles.

1. Wafer defect patterns recognition based on OPTICS and multi-label classification;fan;Proc Adv Inf Manag Commun Electron Autom Control Conf,2017

2. Decision Tree Ensemble-Based Wafer Map Failure Pattern Recognition Based on Radon Transform-Based Features

3. Wafer Map Defect Pattern Classification and Image Retrieval Using Convolutional Neural Network

4. Enhanced Stacked Denoising Autoencoder-Based Feature Learning for Recognition of Wafer Map Defects

5. Wafer Defect Pattern Recognition and Analysis Based on Convolutional Neural Network

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