Ground‐penetrating radar (GPR) is widely used to determine the location of buried pipes
without excavation, and machine learning has been researched to automatically identify the …

Abstract Generative Adversarial Networks (GANs) have emerged as a powerful tool rapidly
advancing the state-of-the-art in numerous domains. This paper conducts a comprehensive …

During the regular service life of high‐speed railway (HSR), there might be serious defects
in the concrete slabs of the infrastructure systems, which may further significantly affect …

Earlier identification of bolt loosening is crucial to maintain structural integrity and prevent
system‐level collapse. In this study, a novel drone‐based 3D vision methodology has been …

High‐resolution (HR) crack images offer more detailed information for assessing structural
conditions compared to low‐resolution (LR) images. This wealth of detail proves …

The segmentation accuracy of bridge crack images is influenced by high‐frequency light,
complex scenes, and tiny cracks. Therefore, an integration–competition network (complex …

This paper presents a framework for estimating the cause of damage to bridge members by
combining Structure from Motion (SfM) and Visual Question Answering (VQA) techniques. A …

Damage detection is essential for the maintenance of transportation infrastructure that
experiences high daily traffic levels in potentially extreme environments and changes in use …

This study presents a novel, deep‐learning‐based model for the automated reconstruction
of a cross‐sectional drawing from stereo photographs. Targeted cross‐sections captured in …

Abstract Neural Radiance Fields (NeRF) techniques demonstrate potential for reconstructing
complex architectural scenes in three dimensions. However, applying NeRF poses …