Performance Optimization and Application Research of YOLOv8 Model in Object Detection

Authors

  • Cheng Jia
  • Defa Wang
  • Jiahao Liu
  • Wenwei Deng

DOI:

https://doi.org/10.54097/p9w3ax47

Keywords:

YOLOv8; object detection; deep learning; computer vision.

Abstract

This paper focuses on the performance optimization and application of the YOLOv8 model in object detection. Firstly, the model architecture and optimization strategies of YOLOv8 are outlined, including network structure, feature extraction, and fusion, demonstrating its advantages in detection accuracy, inference speed, and robustness. Then, the training and inference processes of YOLOv8 are discussed in depth, addressing the issue of imbalance between positive and negative samples, and optimizing the forward propagation and non-maximum suppression algorithm. Through experimental comparisons, YOLOv8 outperforms other mainstream object detection models in multiple metrics. Finally, summarize the contributions and limitations of YOLOv8, and look forward to its future research directions and application prospects. This paper provides valuable references for the optimization and application of the YOLOv8 algorithm, aiming to provide theoretical and practical support for the further development of object detection technology in the field of computer vision.

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References

Wang W, Liu W. 1. In: Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition. ICCPR '23. Association for Computing Machinery; 2024:174-180. doi:10.1145/3633637.3633663

Wu Y, Liao T, Chen F, Zeng H, Ouyang S, Guan J. 2. Electronics.24;13(4):739. doi:10.3390/electronics13040739

Pandey S, Chen KF, Dam EB. 3. In: 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). 2023:2584-2590. doi:10.1109/ICCVW60793.2023.00273

Yanfei P, Yue J. 4. In: 2023 5th International Conference on Artificial Intelligence and Computer Applications (ICAICA). ; 2023:28-32. doi:10.1109/ICAICA58456.2023.10405428

Accessed March 13, 2024. https://ieeexplore.ieee.org/document/10397995

Zhu R, Hao F, Ma D. 6. Agriculture. 2023;13(12):2253. doi:10.3390/agriculture13122253

Lei Bangjun, Yu Ao, Yu Kuai. 7. Radio Engineering: 1-16.

Wang Zeyu, Xu Huiying, Zhu Xinzong, Li Chen, Liu Ziyang, Wang Ziyi. 8. Computer Engineering and Science: 1-17.

Liu Ziyang, Xu Huiying, Zhu Xinzong, et al. 9. Computer Engineering and Science: 1-15.

Zhou Fei, Guo Dudu, Wang Yang, et al. 10. Computer Engineering and Applications. :1-13.

Li Y, Ding M, Zhang Q, et al. 11. Applied Sciences. 2024;14(3):1100. doi:10.3390/app14031100

Gui Xiangquan, Liu Shiqing, Li Li, Qin Qingsong, Li Tangyan. 12. Computer Engineering: 1-11. doi:10.19678/j.issn.1000-3428.0068125

Lin Liheng, Lin Shanling, Lu Beijie, Lin Zhixian, Guo Tailiang. 13. Infrared Technology: 1-8.

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Published

27-03-2024

Issue

Section

Articles

How to Cite

Performance Optimization and Application Research of YOLOv8 Model in Object Detection. (2024). Academic Journal of Science and Technology, 10(1), 325-329. https://doi.org/10.54097/p9w3ax47

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