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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| Main Authors: | , , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
MDPI AG
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/84cf6c3e3cb34491b94582f38c7a3de8 |
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