Abstract:
A pothole is a one of the greatest threat to vehicle drives. It causes an accident by sudden steering of the vehicle wheel, forcing an enormous stress on a vehicle tire o...Show MoreMetadata
Abstract:
A pothole is a one of the greatest threat to vehicle drives. It causes an accident by sudden steering of the vehicle wheel, forcing an enormous stress on a vehicle tire or making a hard turning in a vehicle by late detection. It is crucial to find where a pothole is on the pavement. As the number of pavement increases, detecting a pothole becomes a great challenge in a modern society. Several methods suggest detecting potholes using sensors. However, these methods require an installation on the vehicle in order to collect data of the pavement. Meanwhile, other methods are using smartphone sensors to reduce a cost of deployment and get an advantage of sensitive sensors without a complex installation on the vehicle. For this reason, a method using a smartphone camera with the artificial neural network becomes a way in detecting a pothole on a pavement. In this paper, we investigate the performance in detecting potholes with an image classification method based on the deep convolutional neural network models.
Date of Conference: 12-14 January 2018
Date Added to IEEE Xplore: 29 March 2018
ISBN Information:
Electronic ISSN: 2158-4001