Research on ceramic tile defect detection based on YOLOv3

被引：2
作者：
Li G. [1 ,2 ]
Liu X. [1 ,2 ]
Tao B. [1 ,2 ]
Jiang D. [1 ,2 ]
Zeng F. [1 ,2 ]
Xu S. [1 ,2 ]
机构：
[1] Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education, Wuhan University of Science and Technology, Hubei, Wuhan
[2] Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Hubei, Wuhan
来源：
International Journal of Wireless and Mobile Computing | 2021年 / 21卷 / 02期
关键词：
Artificial intelligence; Defect detection; Project-based teaching; YOLOv3; algorithm;
D O I：
10.1504/IJWMC.2021.120013
中图分类号：
学科分类号：
摘要：
Artificial intelligence is a technology that studies, simulates and expands human intelligence theory and related methods, it is the direction of modern and future science and technology development. The teaching methods of artificial intelligence courses are supposed to be different from the traditional teaching methods, but the actual investigation finds that there are still some problems in the artificial intelligence course, such as the single teaching mode, the low enthusiasm of students for studying, and the poor practical ability of students. In order to solve these issues, this paper applies project teaching methods to an artificial intelligence course, through a specific tile defect detection project to analyse. YOLOv3 algorithm is used to detect six kinds of tile defects, and the experimental results are analysed. Copyright © 2021 Inderscience Enterprises Ltd.
引用
收藏
页码：128 / 133
页数：5
相关论文
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