A deep learning approach for road damage classification

Deep learning techniques, especially convolutional neural networks, have shown good image processing capabilities in recent years. In this work we apply two convolutional models to automatically detect road damages from video frames. The former tries to solve the problem with a semantic segmentation approach while the latter uses an object detection approach. Our results show that the second model could be a valid decision support system to ease the work of human experts.