Knowledge Commons of Institute of Automation,CAS
A Self-Supervised CNN for Particle Inspection on Optical Element | |
Hou W(侯伟); Tao X(陶显); Xu D(徐德) | |
发表期刊 | IEEE Transactions on Instrumentation and Measurement |
ISSN | 0018-9456 |
2021-05 | |
卷号 | 70期号:1页码:1-12 |
通讯作者 | Tao, Xian(taoxian2013@ia.ac.cn) |
摘要 | In high-power laser instruments, optical elements play a significant role. Particles on the optical element degrade the system performance and even cause damage to the optical element. In this article, a particle inspection model based on self-supervised convolutional neural networks (CNNs) and transfer learning is proposed. The self-supervised network that is built on a rotation-flip-invariant pretext task is used to transform the image from grayscale feature to rotation-flip-invariant feature. Then, the learned feature is transferred to the central-pixel classification network that is fine-tuned on a small labeled dataset. The experiments show that the classification accuracy of our proposed method is 97.90%, which is higher than the other compared methods. For the whole image prediction, through feature reuse and pointwise convolution, the central-pixel classification network is adapted to the particle inspection network efficiently with minor changes. Since the method utilizes massive unlabeled data and is fine-tuned on a small number of labeled samples, it has the potential to be used in industrial production. |
关键词 | Inspection Feature reuse optical element particle inspection self-supervised learning transfer learning |
学科门类 | 工学 ; 工学::计算机科学与技术(可授工学、理学学位) |
DOI | 10.1109/TIM.2021.3077994 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Beijing Municipal Natural Science Foundation, China[4212044] ; National Natural Science Foundation of China[62066004] |
项目资助者 | Beijing Municipal Natural Science Foundation, China ; National Natural Science Foundation of China |
WOS研究方向 | Engineering ; Instruments & Instrumentation |
WOS类目 | Engineering, Electrical & Electronic ; Instruments & Instrumentation |
WOS记录号 | WOS:000715343300006 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44874 |
专题 | 中国科学院工业视觉智能装备工程实验室_精密感知与控制 |
通讯作者 | Tao X(陶显) |
作者单位 | 1.中国科学院大学人工智能学院 2.中国科学院自动化研究所 3.中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Hou W,Tao X,Xu D. A Self-Supervised CNN for Particle Inspection on Optical Element[J]. IEEE Transactions on Instrumentation and Measurement,2021,70(1):1-12. |
APA | Hou W,Tao X,&Xu D.(2021).A Self-Supervised CNN for Particle Inspection on Optical Element.IEEE Transactions on Instrumentation and Measurement,70(1),1-12. |
MLA | Hou W,et al."A Self-Supervised CNN for Particle Inspection on Optical Element".IEEE Transactions on Instrumentation and Measurement 70.1(2021):1-12. |
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