RDD2020: An annotated image dataset for automatic road damage detection using deep learning

This data article provides details for the RDD2020 dataset comprising 26,336 road images from India, Japan, and the Czech Republic with more than 31,000 instances of road damage. The dataset captures four types of road damage: longitudinal cracks, transverse cracks, alligator cracks, and potholes; a...

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Detalles Bibliográficos
Autores principales: Arya, Deeksha, Maeda, Hiroya, Ghosh, Sanjay Kumar, Toshniwal, Durga, Sekimoto, Yoshihide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166755/
https://www.ncbi.nlm.nih.gov/pubmed/34095382
http://dx.doi.org/10.1016/j.dib.2021.107133

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166755/
https://www.ncbi.nlm.nih.gov/pubmed/34095382
http://dx.doi.org/10.1016/j.dib.2021.107133

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