基于细胞神经网络的汽车零部件缺陷区域有效检测方法

IF 0.6 4区 计算机科学 Q4 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
Quanyou Zhang, Yong Feng, Lufeng Wang, Yongheng Wang, Bao-hua Qiang, Yaohui Li, Yibin Wang
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引用次数: 0

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An Effective and Efficient Method for Detecting Defective Areas of Auto Parts based on CNNs
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来源期刊
Journal of Imaging Science and Technology
Journal of Imaging Science and Technology 工程技术-成像科学与照相技术
CiteScore
2.00
自引率
10.00%
发文量
45
审稿时长
>12 weeks
期刊介绍: Typical issues include research papers and/or comprehensive reviews from a variety of topical areas. In the spirit of fostering constructive scientific dialog, the Journal accepts Letters to the Editor commenting on previously published articles. Periodically the Journal features a Special Section containing a group of related— usually invited—papers introduced by a Guest Editor. Imaging research topics that have coverage in JIST include: Digital fabrication and biofabrication; Digital printing technologies; 3D imaging: capture, display, and print; Augmented and virtual reality systems; Mobile imaging; Computational and digital photography; Machine vision and learning; Data visualization and analysis; Image and video quality evaluation; Color image science; Image archiving, permanence, and security; Imaging applications including astronomy, medicine, sports, and autonomous vehicles.
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