Deep Learning for Segmentation of Cracks in High-Resolution Images of Steel Bridges

arXiv:2403.17725v1 Announce Type: new
Abstract: Automating the current bridge visual inspection practices using drones and image processing techniques is a prominent way to make these inspections more effective, robust, and less expensive. In this paper, we investigate the development of a novel deep-learning method for the detection of fatigue cracks in high-resolution images of steel bridges. First, we present a novel and challenging dataset comprising of images of cracks in steel bridges. Secondly, we integrate the ConvNext neural network with …

abstract arxiv bridge cs.cv current deep learning detection development drones eess.iv image image processing images novel paper practices processing resolution robust segmentation type visual visual inspection