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...

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Detalles Bibliográficos
Autores principales: Kuric, Ivan, Klarák, Jaromír, Sága, Milan, Císar, Miroslav, Hajdučík, Adrián, Wiecek, Dariusz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587048/
https://www.ncbi.nlm.nih.gov/pubmed/34770379
http://dx.doi.org/10.3390/s21217073

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