![]() ![]() With a small quantity of images, the new approach can rapidly and precisely pick out cracks in the gathered images. proposed a new crack detection approach based completely on the crack central point-particularly, the crack central point approach-to address these critical issues. The new method depends on algorithms of computational intelligence and methods of image processing. Hoang proposed a smart method of automatically classifying road cracks to enhance the effectiveness of periodic surveys of asphalt pavement conditions. In the previous ten years, many scholars have conducted in-depth examinations of road crack recognition primarily based on digital image processing. In the research field of road crack recognition that is primarily based on computer vision, the essential methods mainly include digital image processing methods, which mainly distinguish features manually and employ many feature rules to design some feature recognition conditions, and convolutional networks based on deep learning, which adopt networks to automatically investigate the features of information so that the net can continuously adjust itself according to a certain rule to achieve input data output equal to or close to the label. However, the joint training strategy causes a degradation in the effectiveness of the bounding box detected by Mask R-CNN. The results show that the joint training strategy is very effective, and we are able to ensure that both Faster R-CNN and Mask R-CNN complete the crack detection task when trained with only 130+ images and can outperform YOLOv3. ![]() In this paper, deep learning is investigated to intelligently detect road cracks, and Faster R-CNN and Mask R-CNN are compared and analyzed. ![]() With the technological breakthroughs of general deep learning algorithms in recent years, detection algorithms based on deep learning and convolutional neural networks have achieved better results in the field of crack recognition. In recent years, the recognition of road pavement cracks based on computer vision has attracted increasing attention. The intelligent crack detection method is an important guarantee for the realization of intelligent operation and maintenance, and it is of great significance to traffic safety. ![]()
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