Multi-level joint distributed alignment-based domain adaptation for cross-scenario strip defect recognition
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hebei Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10845-024-02344-z.pdf
Reference47 articles.
1. Boschetto, A., Bottini, L., & Vatanparast, S. (2023). Powder bed monitoring via digital image analysis in additive manufacturing. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-023-02091-7
2. Boudani, F. Z., Nacereddine, N., & Laiche, N. (2021). Content-Based Image Retrieval for Surface Defects of Hot Rolled Steel Strip Using Wavelet-Based LBP. In Progress in Artificial Intelligence and Pattern Recognition: 7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021, Havana, Cuba. pp. 404–413. https://doi.org/10.1007/978-3-030-89691-1_39
3. Chu, T., Liu, Y., Deng, J., Li, W., & Duan, L. (2022, June). Denoised Maximum Classi?er Discrepancy for Source-Free Unsupervised Domain Adaptation. Proceedings of the AAAI Conference on Artificial Intelligence 36(1), 472–480. https://doi.org/10.1609/aaai.v36i1.19925
4. Cui, S., Wang, S., Zhuo, J., Su, C., Huang, Q., & Tian, Q. (2020). Gradually vanishing bridge for adversarial domain adaptation. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA (pp. 12452–12461). https://doi.org/10.1109/CVPR42600.2020.01247
5. Czimmermann, T., Ciuti, G., Milazzo, M., Chiurazzi, M., Roccella, S., Oddo, C. M., & Dario, P. (2020). Visual-based defect detection and classification approaches for industrial applications: A survey. Sensors, 20(5), 1459. https://doi.org/10.3390/s20051459
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