Monitoring expressway surfaces is essential for ensuring the comfort and security of all road consumers, including boats and pedestrians. Furthermore, the maintenance of the roadways will benefit from this knowledge. As a result of the changeable weather, the state of the roads diminishes. Thus, producing an representation dataset of the road surface for two seasons-vacation and moist-thus serves as the main goal of the submitted paper. Consequently, we produced photos and videos of miscellaneous road surfaces, containing paved and unpaved roads. These folders have two subfolders for potholes in the moist and summer seasons. The dataset resides of 10 videos and 8484 pictures. For machine learning consultants working in the fields of automatic taxi control and road surface listening, this dataset is quite constructive.
Author(s) Details:
Sonali Bhutad,
Vishwakarma
University, Pune, India.
Kailas
Patil,
Vishwakarma
University, Pune, India.
Please see the link here: https://stm.bookpi.org/RHST-V9/article/view/11681
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