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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Vydáno v:Data in brief Ročník 36; s. 107133
Hlavní autoři: Arya, Deeksha, Maeda, Hiroya, Ghosh, Sanjay Kumar, Toshniwal, Durga, Sekimoto, Yoshihide
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.06.2021
Elsevier
Témata:
alligators
Automatic road condition monitoring
Crack recognition
Czech Republic
Data
data collection
Data qualification
Deep learning
image analysis
India
Japan
mobile telephones
Pavement surface condition assessment
pavements
Quantification
Road damage dataset
Road infrastructure
Smartphone-based road damage detection and classification
Structural health monitoring
Czech Republic
India
Deep learning
Road damage dataset
Smartphone-based road damage detection and classification
Quantification
Data qualification
Structural health monitoring
Crack recognition
Image
Road infrastructure
Automatic road condition monitoring
Pavement surface condition assessment
ISSN:2352-3409, 2352-3409
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Popis
Shrnutí: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; and is intended for developing deep learning-based methods to detect and classify road damage automatically. The images in RDD2020 were captured using vehicle-mounted smartphones, making it useful for municipalities and road agencies to develop methods for low-cost monitoring of road pavement surface conditions. Further, the machine learning researchers can use the datasets for benchmarking the performance of different algorithms for solving other problems of the same type (image classification, object detection, etc.). RDD2020 is freely available at [1]. The latest updates and the corresponding articles related to the dataset can be accessed at [2].
Bibliografie:ObjectType-Article-1
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ObjectType-Feature-2
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ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2021.107133