A Survey of Surface Defect Detection Based on Deep Learning

DOI

10.2991/978-2-494069-51-0_51How to use a DOI?

Keywords

Machine vision; Surface defect detection; Deep learning; Convolutional neural network (CNN)

Abstract

In recent years, with the rapid development of technologies such as computers and artificial intelligence, various research fields based on deep learning have been broadly used, among which industrial detection is the most important. In this paper, the definition of defects and defect detection is firstly defined. Then, several mainstream methods of surface defect detection based on convolutional neural network are introduced in recent years, and the typical application scenarios of each method are summarized. Finally, two key problems in surface defect detection are discussed.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Weihua Yang
PY  - 2022
DA  - 2022/12/09
TI  - A Survey of Surface Defect Detection Based on Deep Learning
BT  - Proceedings of the 2022 7th International Conference on Modern Management and Education Technology (MMET 2022)
PB  - Atlantis Press
SP  - 362
EP  - 367
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-51-0_51
DO  - 10.2991/978-2-494069-51-0_51
ID  - Yang2022
ER  -