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Publication Detailed Description
RoadDamageVision: Annotated Dataset of Road Damage Images
Year (definitive publication)
2026
Language
English
Country
United States of America
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Abstract
This dataset was developed under the hypothesis that deep learning and computer vision techniques can be effectively used to detect and classify various types of road surface defects from drone-based visual data. By providing annotated images captured in different countries and environments using aerial platforms, the RoadDamageVision dataset supports the development of scalable, low-cost, and automated road monitoring systems.
Acknowledgements
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Report Type
International project anual report
Keywords
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences
- Other Engineering and Technology Sciences - Engineering and Technology
- Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Contributions to the Sustainable Development Goals of the United Nations
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