Lightweight deep learning for real-time road distress detection on mobile devices
Abstract Efficient and accurate road distress detection is crucial for infrastructure maintenance and transportation safety. Traditional manual inspections are labor-intensive and time-consuming, while increasingly popular automated systems often rely on computationally intensive devices, limiting w...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-59516-5 |
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