Efficient Deep Learning Methods for Identification of Defective Casting Products
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-22405-8_13
Reference17 articles.
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3. Wang, T., Chen, Y., Qiao, M., Snoussi, H.: A fast and robust convolutional neural network-based defect detection model in product quality control. Int. J. Adv. Manuf. Technol. 94(9–12), 3465–3471 (2017). https://doi.org/10.1007/s00170-017-0882-0
4. Du, W., Shen, H., Fu, J., Zhang, G., He, Q.: Approaches for improvement of the X-ray image defect detection of automobile casting aluminum parts based on deep learning. NDT and E International 107, no. May, p. 102144 (2019). https://doi.org/10.1016/j.ndteint.2019.102144
5. Tout, K.: Automatic vision system for surface inspection and monitoring : application to wheel inspection To cite this version (2018)
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