Design and fabrication of a high-efficiency defect inspection prototype for diary plastic cutlery based on machine-vision with improved deep leaning algorithm
Author:
Funder
Jiangsu Key R&D Program
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-19395-2.pdf
Reference31 articles.
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2. Yun JP, Shin WC, Koo G et al (2020) Automated defect inspection system for metal surfaces based on deep learning and data augmentation[J]. J Manuf Syst 55:317–324. https://doi.org/10.1016/j.jmsy.2020.03.009
3. Ravimal D, Kim H, Koh D et al (2020) Image-based inspection technique of a machined metal surface for an unmanned lapping process[J]. Int J Precision Eng Manuf-Green Technol 7:547–557. https://doi.org/10.1016/j.jmsy.2020.03.009
4. Miao R, Shan Z, Zhou Q et al (2022) Real-time defect identification of narrow overlap welds and application based on convolutional neural networks[J]. J Manuf Syst 62:800–810. https://doi.org/10.1016/j.jmsy.2021.01.012
5. Javaid M, Haleem A, Singh RP et al (2022) Exploring impact and features of machine vision for progressive industry 4.0 culture[J]. Sensors Int 3:100132. https://doi.org/10.1016/j.sintl.2021.100132
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