A Review on Industrial Surface Defect Detection Based on Deep Learning Technology-Reference-Cited by-同舟云学术

A Review on Industrial Surface Defect Detection Based on Deep Learning Technology

Published:2020-09-18 Issue: Volume: Page:
ISSN:
Container-title:2020 The 3rd International Conference on Machine Learning and Machine Intelligence
language:
Short-container-title:

Author:

Qi Shengxiang¹,Yang Jiarong²,Zhong Zhenyi²

Affiliation:

1. Shanghai Electric Group Co.Ltd.Central Academe, China

2. Shanghai Electric Group Co. Ltd. Central Academe, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3426826.3426832

Reference48 articles.

1. LeCun Y. Bengio Y. Hinton G. 2015. Deep learning. Nature. 521 (May. 2015) 436-444. https://doi.org/10.1038/nature14539. LeCun Y. Bengio Y. Hinton G. 2015. Deep learning. Nature. 521 (May. 2015) 436-444. https://doi.org/10.1038/nature14539.

2. Guo Y. Liu Y. Oerlemans A. 2016. Deep learning for visual understanding: a review. Neurocomputing. 187 (Apr. 2016) 27-48. https://doi.org/10.1016/j.neucom.2015.09.116. Guo Y. Liu Y. Oerlemans A. 2016. Deep learning for visual understanding: a review. Neurocomputing. 187 (Apr. 2016) 27-48. https://doi.org/10.1016/j.neucom.2015.09.116.

3. Gu J. Wang Z. Kuen J. 2018. Recent advances in convolutional neural networks. Pattern Recognition. 77 (May. 2018) 354-377. https://doi.org/10.1016/j.patcog.2017.10.013. Gu J. Wang Z. Kuen J. 2018. Recent advances in convolutional neural networks. Pattern Recognition. 77 (May. 2018) 354-377. https://doi.org/10.1016/j.patcog.2017.10.013.

4. Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

5. Krizhevsky A. Sutskever I. Hinton G. E. 2012. ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems (2012) 1097-1105. Krizhevsky A. Sutskever I. Hinton G. E. 2012. ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems (2012) 1097-1105.

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sustainable Machine Vision for Industry 4.0: A Comprehensive Review of Convolutional Neural Networks and Hardware Accelerators in Computer Vision;AI;2024-08-01

2. Efficient surface defect detection in industrial screen printing with minimized labeling effort;Integrated Computer-Aided Engineering;2024-07-21

3. Predicting Rail Corrugation Based on Convolutional Neural Networks Using Vehicle’s Acceleration Measurements;Sensors;2024-07-17

4. Deep learning-supported machine vision-based hybrid system combining inhomogeneous 2D and 3D data for the identification of surface defects;Production & Manufacturing Research;2024-07-12

5. A new online detection method of tobacco impurities for tobacco robot;Frontiers in Neurorobotics;2024-06-07