Research on Target Detection Method Based on Improved YOLOv5-Reference-Cited by-同舟云学术

Research on Target Detection Method Based on Improved YOLOv5

Published:2022 Issue: Volume: Page:453-461
ISSN:0302-9743
Container-title:Web Information Systems and Applications
language:
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Author:

Wang Rongzhuang,Liu Jun,Zhang Hualiang

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-20309-1_40

Reference12 articles.

1. Guo, L., Wang, Q., Xue, W., Guo, J.: Small target detection algorithm based on improved YOLOv5. J. Univ. Electron. Sci. Technol. 51(02), 251–258 (2022)

2. Li, A.: Improvement of YOLOv5 algorithm and its practical application. Zhongbei University (2021). https://doi.org/10.27470/d.cnki.ghbgc.2021.000232

3. Jin, R., Niu, Q., Spagnolo, P.: Automatic fabric defect detection based on an improved YOLOv5. Math. Probl. Eng. 2021 (2021)

4. Yuan, Z., Fang, W., Zhao, Y., Sheng, V.S.: Research of insect recognition based on improved YOLOv5. J. Artif. Intell. 3(4), 145 (2021)

5. Lv, Z., Li, H., Liu, Y.: Garbage detection and classification method based on YoloV5 algorithm. Tianjin University of Technology and Education (China), Institut für Technische Optik (Germany), Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation), Sichuan University (China) (2022)

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