Overview on Machine Vision Based Surface Defect Detection and Quality Classification in the Leather Manufacturing Process-Reference-Cited by-同舟云学术

Overview on Machine Vision Based Surface Defect Detection and Quality Classification in the Leather Manufacturing Process

Published:2022 Issue: Volume: Page:344-356
ISSN:0302-9743
Container-title:Advances in Visual Computing
language:
Short-container-title:

Author:

Smith A. D.,Du S.,Kurien A.

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-20716-7_27

Reference41 articles.

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2. Moganam, P.K., Seelan, D.A.S.: Perceptron neural network based machine learning approaches for leather defect detection and classification. Instrum. Mes. Métrol. 16(6), 421–429 (2020). https://doi.org/10.18280/i2m.190603

3. Liong, S., Gan, Y.S., Huang, Y., Liu, K., Yau, W.: Integrated neural network and machine vision approach for leather defect classification. ArXiv, abs/1905.11731 (2019)

4. Ingram, K.K., et al.: Molecular insights into chronotype and time-of-day effects on decision-making. Sci. Rep. 6 (2016)

5. Aslam, M., Khan, T.M., Naqvi, S.S., Holmes, G., Naffa, R.: On the application of automated machine vision for leather defect inspection and grading: a survey. IEEE Access 7, 176065–176086 (2019)

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