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...
Enregistré dans:
| Auteurs principaux: | , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/84cf6c3e3cb34491b94582f38c7a3de8 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|