Author:
Chiu Yuan-Shyi,Lin Yu-Kai,Lin Hong-Dar
Publisher
Centre for Evaluation in Education and Science (CEON/CEES)
Subject
Mechanical Engineering,General Engineering,Safety, Risk, Reliability and Quality,Transportation,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering
Reference27 articles.
1. Huang, S.H., Pan, Y.C. (2015). Automated visual inspection in the semiconductor industry: A survey. Computer in Industry, 66, 1-10.;
2. Neogi, N., Mohanta, D.K., Dutta, P.K. (2014). Review of vision-based steel surface inspection systems. EURASIP Journal on Image and Video Processing, 50(1), 1-19.;
3. Lin, H.D., Chiu, S.W. (2011). Automated surface micro flaw inspection for quality control of electronic chips.International Journal of the Physical Sciences, 6(23), 5528-5539.;
4. Lin, H., Li, B., Wang, X.G., Shu, Y.F., Niu, S.L. (2019). Automated defect inspection of LED chip using deep convolutional neural network. Journal of Intelligent Manufacturing, 30(6), 2525-2534.;
5. Park, J.K., Kwon, B.K., Park, J.H., Kang, D.J. (2016). Machine learning-based imaging system for surface defect inspection.International Journal of Precision Engineering and Manufacturing-Green Technology, 3(3), 303-310.;
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