RADNet: Adaptive Spatial-Dilation Learning for Efficient Road Crack Detection
Road crack detection is crucial for infrastructure maintenance and traffic safety, yet existing methods struggle to balance detection accuracy and computational efficiency due to complex texture similarities between cracks and road surfaces. In this paper, we propose RADNet, a lightweight framework...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10942320/ |
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