Potholes on roads constitute a serious problem for citizens acting as pedestrians furthermore as vehicular drivers. Government bodies which carries with it engineers and workers are responsible to detect damages on roads. Manually assessing every single a part of the road is very time- consuming, requires lots of manpower and hence it cannot be done efficiently. the tactic to repair this issue by automating the detection. The study focuses on collecting and analyzing the dataset of potholes to coach a convolutional neural network. the thing detection system tiny YOLOv3 is employed for detecting the potholes. the look of a system is identified which may be used for developing a mobile application for detection and presenting a visualized view of the potholes.
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Pothole Detection Using Yolo V3: A Deep Learning Approach
Semantic Scholar · Computer Science · 2021
Abstract
Potholes on roads constitute a serious problem for citizens acting as pedestrians furthermore as vehicular drivers. Government bodies which carries with it engineers and workers are responsible to detect damages on roads. Manually assessing every single a part of the road is very time- consuming, requires lots of manpower and hence it cannot be done efficiently. the tactic to repair this issue by automating the detection. The study focuses on collecting and analyzing the dataset of potholes to coach a convolutional neural network. the thing detection system tiny YOLOv3 is employed for detecting the potholes. the look of a system is identified which may be used for developing a mobile application for detection and presenting a visualized view of the potholes.