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Conductive Particle Detection for Chip on Glass Using Convolutional Neural Network | |
Tao X(陶显)1![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
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ISSN | 0018-9456 |
2021-06 | |
卷号 | 70期号:1页码:1-10 |
文章类型 | 长文 |
摘要 | The detection of conductive particle images is an important part of the chip on glass (COG) process and can be used to ensure the performance of electrical connections. The segmentation of conductive particles is essential but a difficult task, since the scale and edge of the conductive particles on the chip and the imaging effect are different. In recent years, methods based on deep learning have become the representative method of image segmentation. However, the currently existing methods cannot fully consider the characteristics of conductive particles and have high model complexity. In this article, a multi-frequency feature learning-based convolutional neural network (CNN) is proposed. The entire network structure consists of a basic U-Net module and multi-frequency module (MFM), which are used to enhance multi-frequency feature fusion of conductive particles and accelerate network training. At the same time, for the feature of particle shape, an active contour without edge (ACWE) loss function is designed to extract the fine contour feature of particles. Experimental results on three datasets show the superiority of the proposed method over the major existing mainstream methods with respect to the three performance indicators: recall, precision, and Intersection-over-Union (IoU). |
关键词 | 缺陷检测 |
学科门类 | 工学 |
DOI | 10.1109/TIM.2021.3086908 |
URL | 查看原文 |
收录类别 | SCIE |
语种 | 英语 |
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/173211/47201 |
专题 | 中科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.Institute of Automation, Chinese Academy of Sciences 2.China University of Mining and Technology, Beijing |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Tao X,Ma WZ,Lu ZF,et al. Conductive Particle Detection for Chip on Glass Using Convolutional Neural Network[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2021,70(1):1-10. |
APA | Tao X,Ma WZ,Lu ZF,&Hou ZX.(2021).Conductive Particle Detection for Chip on Glass Using Convolutional Neural Network.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,70(1),1-10. |
MLA | Tao X,et al."Conductive Particle Detection for Chip on Glass Using Convolutional Neural Network".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 70.1(2021):1-10. |
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Conductive_Particle_(3208KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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