Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks
文献类型：期刊论文
| 作者 | Zhang ZT(张正涛) ; Zhang ZT(张正涛)
|
| 刊名 | Jounral of Precision Engineering and Manufacturing
 |
| 出版日期 | 2018 |
| 卷号 | 19期号:6页码:801-810 |
| 关键词 | Mobile Phone Cover Glass Defect Inspection Deep Learning Sementic Segmentation |
| 英文摘要 |
The emergency of surface defect would significantly influence the quality of MPCG
(Mobile Phone Cover Glass). Therefore, efficient defect detection is highly required in
the manufacturing process. Focusing on the problem, an automatic detection system is
developed in this paper. The system adopts backlight imaging technology to improve
the signal to noise ration and imaging effect. Then, a modified segmentation method is
presented for defect extraction and measurement based on deep neural networks. In
the method, a novel data generation process is provided, with which the drawback that
huge amount of data is required for training deep structured networks can be
overcome. Finally, experiments are well conducted to verify that satisfactory
performance is achieved with the proposed method. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21666]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 通讯作者 | Zhang ZT(张正涛) |
| 推荐引用方式 GB/T 7714 | Zhang ZT,Zhang ZT. Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks[J]. Jounral of Precision Engineering and Manufacturing,2018,19(6):801-810. |
| APA | Zhang ZT,&张正涛.(2018).Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks.Jounral of Precision Engineering and Manufacturing,19(6),801-810. |
| MLA | Zhang ZT,et al."Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks".Jounral of Precision Engineering and Manufacturing 19.6(2018):801-810. |
入库方式： OAI收割
来源：自动化研究所
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