Autoencoder-Based Unsupervised Surface Defect Detection Using Two-Stage Training
Author:
Affiliation:
1. School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
2. Key Laboratory of Computer Network and Information Integration, Southeast University, Ministry of Education, Nanjing 211189, China
Abstract
Funder
This work is supported by the Significant Science And Technology Project of Nanjing
Publisher
MDPI AG
Link
https://www.mdpi.com/2313-433X/10/5/111/pdf
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5. Chen, Y., Ding, Y., Zhao, F., Zhang, E., Wu, Z., and Shao, L. (2021). Surface defect detection methods for industrial products: A review. Appl. Sci., 11.
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