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Rewrite Lightweight deep learning for real-time road distress detection on mobile devices as a headline for a science magazine post, using no more than 8 words

May 6, 2025
in Earth Science
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Hu, Y., Chen, N., Hou, Y. et al. Lightweight deep learning for real-time road distress detection on mobile devices.
Nat Commun 16, 4212 (2025).

bu içeriği en az 2500 kelime olacak şekilde ve alt başlıklar ve madde içermiyecek şekilde ünlü bir science magazine için İngilizce olarak yeniden yaz. Teknik açıklamalar içersin ve viral olacak şekilde İngilizce yaz. Haber dışında başka bir şey içermesin. Haber içerisinde en az 14 paragraf ve her bir paragrafta da en az 80 kelime olsun. Cevapta sadece haber olsun. Ayrıca haberi yazdıktan sonra içerikten yararlanarak aşağıdaki başlıkların bilgisi var ise haberin altında doldur. Eğer bilgi yoksa ilgili kısmı yazma.:

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Hu, Y., Chen, N., Hou, Y. et al. Lightweight deep learning for real-time road distress detection on mobile devices.
Nat Commun 16, 4212 (2025). https://doi.org/10.1038/s41467-025-59516-5

Image Credits: AI Generated

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Tags: AI in transportationcomputer vision in road monitoringdeep learning algorithmslightweight deep learningmachine learning applicationsmobile computing advancementsmobile device technologypredictive maintenance for roadsreal-time road distress detectionroad safety innovationssmart transportation systemsurban infrastructure management
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