A Comparative Study of YOLOv5 and YOLOv8 for Appearance Defect Detection in Polyester Fiber Yarn Packages-Reference-Cited by-同舟云学术

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A Comparative Study of YOLOv5 and YOLOv8 for Appearance Defect Detection in Polyester Fiber Yarn Packages

Published:2023-12-16 Issue: Volume:4 Page:96-99
ISSN:
Container-title:2023 16th International Symposium on Computational Intelligence and Design (ISCID)
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Author:

Jiangchen Gu¹,Zhongliang Yang¹

Affiliation:

1. Donghua University, Shanghai,College of Mechanical Engineering,China Shanghai,China,201620

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10494045/10494046/10494278.pdf?arnumber=10494278

Reference12 articles.

1. Discussion AND Research of Reducing the Pure Chemical Fibre Yarn Hairiness;Zhao;Chemical Fiber & Textile Technology,2007

2. Detection of yarn hairiness combining microscopic vision and attention mechanism;Tang;CAAI Transactions on Intelligent Systems,2022

3. Surface defect recognition of chemical fiber yarn packages based on improved convolutional neural network;Wang;Journal of textile research,2020

4. Hairiness detection of chemical fiber DTY packages using laser triangulation;Zhang;Journal of Xian Polytechnic University,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A comparative study of YOLOv5 and YOLOv8 for corrosion segmentation tasks in metal surfaces;Array;2024-07

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