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Title	Research On Road Pothole Recognition Based On Deep Convolutional Neural Networks
ID_Doc	45593
Authors	Liu J.; Wang H.; Wei J.; Nan J.
Year	2024
Published	2024 IEEE 2nd International Conference on Image Processing and Computer Applications, ICIPCA 2024
DOI	http://dx.doi.org/10.1109/ICIPCA61593.2024.10708995
Abstract	This paper focuses on the urban road pothole detection problem and develops a computer vision-based pothole detection model using deep learning methods. First, a pre-trained EfficientNetBO convolutional neural network is used as a feature extractor and combined with a target detection framework to learn and test the road images; second, the generalization ability of the model to unknown data is effectively improved by image enhancement techniques such as random cropping, rotating, and flipping; lastly, experiments show that the model has an accuracy of more than 90% on a number of test sets, and especially in the complex scenes outperforms traditional methods, showing good robustness and generalization ability, which provides important technical support for smart city management. © 2024 IEEE.
Author Keywords	computer vision; deep learning; product neural network; Road pothole detection

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