Performance Evaluation of Transfer Learning for Surface Defect Classification-Reference-Cited by-同舟云学术

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Performance Evaluation of Transfer Learning for Surface Defect Classification

Published:2022 Issue: Volume: Page:977-988
ISSN:2367-3370
Container-title:Innovations in Smart Cities Applications Volume 5
language:
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Author:

Benbarrad Tajeddine,Arioua Mounir,Anas Hatim

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-94191-8_79

Reference20 articles.

1. D.L. Galata et al., Applications of machine vision in pharmaceutical technology: a review. Eur. J. Pharm. Sci. 159, 105717 (2021). https://doi.org/10.1016/j.ejps.2021.105717

2. D. Bini, D. Pamela, S. Prince, Machine vision and machine learning for intelligent agrobots: a review, in 2020 5th International Conference on Devices, Circuits and Systems (ICDCS) (20200, pp. 12–16. https://doi.org/10.1109/ICDCS48716.2020.243538

3. T. Benbarrad, M. Salhaoui, S.B. Kenitar, M. Arioua, Intelligent machine vision model for defective product inspection based on machine learning. J. Sens. Actuat. Netw. 10(1), 7 (2021). https://doi.org/10.3390/jsan10010007

4. T.-H. Kim, H.-R. Kim, Y.-J. Cho, Product inspection methodology via deep learning: an overview. Sensors 21(15), 5039 (2021). https://doi.org/10.3390/s21155039

5. X. Zheng, S. Zheng, Y. Kong, J. Chen, Recent advances in surface defect inspection of industrial products using deep learning techniques. Int. J. Adv. Manuf. Technol. 113(1–2), 35–58 (2021). https://doi.org/10.1007/s00170-021-06592-8

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