CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 13229 > Article
Paper
7 August 2024 YOLOv8n-EMA-ODC wafer defect classification model
Yuanyuan Li, Qiangkui Leng, Jianxu Lu
Author Affiliations +
Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 1322902 (2024) https://doi.org/10.1117/12.3038166
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China
Abstract
Wafer defect classification is a critical issue in the semiconductor field, yet the detection accuracy of existing methods still can be improved. In this paper, a novel method based on YOLOv8n is proposed, it integrates the EMA mechanism and ODConv. The EMA mechanism assigns higher weights to important features to enhance accuracy, while ODConv reduces computational complexity through parallel computation. Experimental results on the WM-811k dataset demonstrate that our method achieves an accuracy rate of 97.5%, which represents a 2.2% higher accuracy than the baseline model, while reducing computational complexity by approximately 27% compared to the baseline model. This result confirms that the proposed method can maintain high accuracy in the semiconductor field while having lower computational complexity.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Yuanyuan Li, Qiangkui Leng, and Jianxu Lu "YOLOv8n-EMA-ODC wafer defect classification model", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 1322902 (7 August 2024); https://doi.org/10.1117/12.3038166
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 9 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Semiconducting wafers
Feature extraction
Defect detection
Deep learning
Image classification
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top