Prediction of Wafer Map Categories Using Wafer Acceptance Test Parameters in Semiconductor Manufacturing
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-08337-2_12
Reference12 articles.
1. Shim, J., Kang, S., Cho, S.: Active learning of convolutional neural network for cost-effective wafer map pattern classification. IEEE Trans. Semicond. Manuf. 33(2), 258–266 (2020). https://doi.org/10.1109/TSM.2020.2974867
2. Chen, L.L.-Y., et al.: Semi-supervised framework for wafer defect pattern recognition with enhanced labeling. In: 2021 IEEE International Test Conference (ITC), pp. 208–212 (2021).https://doi.org/10.1109/ITC50571.2021.00029
3. Chien, C.-F., Lee, P.-C., Dou, R., Chen, Y.-J., Chen, C.-C.: Modeling collinear WATs for parametric yield enhancement in semiconductor manufacturing. In: 2017 13th IEEE Conference on Automation Science and Engineering (CASE), pp. 739–743 (2017). https://doi.org/10.1109/COASE.2017.8256192
4. Chen, X., Zhao, Y., Lü, H., Shao, X., Chen, C., Huang, Y.: A machine learning-based approach for failure prediction at cell level based on wafer acceptance test parameters. In: 2021 IEEE Microelectronics Design & Test Symposium (MDTS), pp. 1–52021https://doi.org/10.1109/MDTS52103.2021.9476151
5. Jiang, D., Lin, W., Raghavan, N.: A novel framework for semiconductor manufacturing final test yield classification using machine learning techniques. IEEE Access 8, 197885–197895 (2020)
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