Enhanced convolutional neural networks for defect detection in fiber-reinforced composites: a hyperparameter optimization approach
Abstract Fiber-reinforced composites are widely utilized in aerospace, automotive, and structural applications due to their superior strength-to-weight ratio. Despite their advantages, they are prone to internal defects such as fiber-matrix separation, fiber breakage, fiber pullout, void formation,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
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| Series: | Journal of Engineering and Applied Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44147-025-00698-6 |
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