Automated defect detection on inductive thermography images using supervised and semi-supervised Deep Learning methods
Inductive infrared thermography has been proven as an interesting solution for the inspection of surface defects. To automate the inspection, defect detection methods based on convolutional neural network proved their efficiency for complex detection tasks compared to traditional methods. Both supe...
| Main Authors: | , , |
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| Format: | Article |
| Language: | deu |
| Published: |
NDT.net
2023-09-01
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| Series: | e-Journal of Nondestructive Testing |
| Online Access: | https://www.ndt.net/search/docs.php3?id=28510 |