Rs-net: Residual Sharp U-Net architecture for pavement crack segmentation and severity assessment

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Rs-net: Residual Sharp U-Net architecture for pavement crack segmentation and severity assessment ; volume:11 ; number:1 ; day:17 ; month:8 ; year:2024 ; pages:1-27 ; date:12.2024
Journal of Big Data ; 11, Heft 1 (17.8.2024), 1-27, 12.2024

Creator: Ali, Luqman
AlJassmi, Hamad
Swavaf, Mohammed
Khan, Wasif
Alnajjar, Fady

Contributor: SpringerLink (Online service)

DOI: 10.1186/s40537-024-00981-y

URN: urn:nbn:de:101:1-2411042106308.280788503459

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:41 AM CEST

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Ali, Luqman
AlJassmi, Hamad
Swavaf, Mohammed
Khan, Wasif
Alnajjar, Fady
SpringerLink (Online service)

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Rs-net: Residual Sharp U-Net architecture for pavement crack segmentation and severity assessment

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