Image-Based Pavement Type Classification with Convolutional Neural Networks
2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)(2020)
摘要
Road pavement type classification is important in route planning, road maintenance and for autonomous vehicles. In this paper, we propose a deep learning based method for automatic road type classification from road surface images. The resulting binary classifiers (paved and non-paved road classes) achieve up to 98% classification accuracy on the test set that contains over 100 000 real-world road images that cover a distance of over 300 km.
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关键词
Roads,Cameras,Image segmentation,Feature extraction,Training,Machine learning,Task analysis
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