Optimizing surface defect detection with YOLOv9: the role of advanced backbone models
- DOI
- 10.3389/frai.2025.1675154
- Published
- 2025-10-10
- Container
- Frontiers in Artificial Intelligence
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/frai.2025.1675154,
title = {Optimizing surface defect detection with YOLOv9: the role of advanced backbone models},
author = {Zhonglin Zeng and Hongyang Wang and Chi Yao and Zile Dong and Shimin Cai},
year = {2025},
journal = {Frontiers in Artificial Intelligence},
doi = {10.3389/frai.2025.1675154},
url = {https://doi.org/10.3389/frai.2025.1675154}
}RIS
TY - JOUR TI - Optimizing surface defect detection with YOLOv9: the role of advanced backbone models AU - Zhonglin Zeng AU - Hongyang Wang AU - Chi Yao AU - Zile Dong AU - Shimin Cai PY - 2025 JO - Frontiers in Artificial Intelligence DO - 10.3389/frai.2025.1675154 UR - https://doi.org/10.3389/frai.2025.1675154 ER -
APA
Zeng, Z., Wang, H., Yao, C., Dong, Z., & Cai, S. (2025). Optimizing surface defect detection with YOLOv9: the role of advanced backbone models. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2025.1675154
Source records
- crossref · retrieved 2026-09-26T23:52:31.208Z