Defect classification on limited labeled samples with multiscale feature fusion and semi-supervised learning
Author:
Funder
National Program on Key Basic Research Project
Key-Area Research and Development Program of Guangdong Province
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-02917-y.pdf
Reference47 articles.
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3. Di H, Ke X, Peng Z, Dongdong Z (2019) Surface defect classification of steels with a new semi-supervised learning method. Opt Lasers Eng 117:40–48
4. Dong H, Song K, He Y, et al (2019) PGA-Net: Pyramid feature fusion and global context attention network for automated surface defect detection[J]. IEEE Transactions on Industrial Informatics 16(12):7448–7458
5. Lee H, Ryu K (2020) Dual-Kernel-Based Aggregated Residual Network for Surface Defect Inspection in Injection Molding Processes. Appl Sci 10:8171
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