An optimized YOLOv8n based model for real time defect detection in taro strip production
Abstract Taro production is predominantly manual, creating a need for automated defect detection in processing lines to improve efficiency and product quality. Traditional computer vision methods lack accuracy under practical industrial production conditions, while deep learning approaches, though r...
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| Auteurs principaux: | , , , , , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Nature Portfolio
2025-12-01
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| Collection: | Scientific Reports |
| Sujets: | |
| Accès en ligne: | https://doi.org/10.1038/s41598-025-28216-x |
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