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Analysis of the Possibilities of Tire-Defect Inspection Based on Unsupervised Learning and Deep Learning
At present, inspection systems process visual data captured by cameras, with deep learning approaches applied to detect defects. Defect detection results usually have an accuracy higher than 94%. Real-life applications, however, are not very common. In this paper, we describe the development of a ti...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587048/ https://www.ncbi.nlm.nih.gov/pubmed/34770379 http://dx.doi.org/10.3390/s21217073 |