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Research on steel rail surface defects detection based on improved YOLOv4 network
INTRODUCTION: The surface images of steel rails are extremely difficult to detect and recognize due to the presence of interference such as light changes and texture background clutter during the acquisition process. METHODS: To improve the accuracy of railway defects detection, a deep learning algo...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947530/ https://www.ncbi.nlm.nih.gov/pubmed/36845065 http://dx.doi.org/10.3389/fnbot.2023.1119896 |