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Muhammad Abi Berkah Nadi, Sayed Ahmad Fauzan
Pág. 1 - 9
Recovery efforts following a disaster can be slow and painstaking work, and potentially put responders in harm's way. A system which helps identify defects in critical building elements (e.g., concrete columns) before responders must enter a structure ca...
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Xunqian Xu, Qi Li, Shue Li, Fengyi Kang, Guozhi Wan, Tao Wu and Siwen Wang
Based on the tunnel crack width identification, there are operating time constraints, limited operating space, high equipment testing costs, and other issues. In this paper, a large subway tunnel is a research object, and the tunnel rail inspection car i...
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Rong Wang, Xinyang Zhou, Yi Liu, Dongqi Liu, Yu Lu and Miao Su
To ensure the safety and durability of concrete structures, timely detection and classification of concrete cracks using a low-cost and high-efficiency method is necessary. In this study, a concrete surface crack damage detection method based on the ResN...
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Jianyuan Li, Xiaochun Lu, Ping Zhang and Qingquan Li
The timely identification and detection of surface cracks in concrete dams, an important public safety infrastructure, is of great significance in predicting engineering hazards and ensuring dam safety. Due to their low efficiency and accuracy, manual de...
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Xinjian Xiang, Haibin Hu, Yi Ding, Yongping Zheng and Shanbao Wu
This study proposes a GC-YOLOv5s crack-detection network of UAVs to work out several issues, such as the low efficiency, low detection accuracy caused by shadows, occlusions and low contrast, and influences due to road noise in the classic crack-detectio...
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Ugne Orinaite, Vilte Karaliute, Mayur Pal and Minvydas Ragulskis
This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, such as offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams, etc. Our ...
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Yingxiang Zhao, Lumei Zhou, Xiaoli Wang, Fan Wang and Gang Shi
Cracks are a common type of road distress. However, the traditional manual and vehicle-borne methods of detecting road cracks are inefficient, with a high rate of missed inspections. The development of unmanned aerial vehicles (UAVs) and deep learning ha...
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Jingying Zhang and Tengfei Bao
Crack detection is an important component of dam safety monitoring. Detection methods based on deep convolutional neural networks (DCNNs) are widely used for their high efficiency and safety. Most existing DCNNs with high accuracy are too complex for use...
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Hui Luo, Jiamin Li, Lianming Cai and Mingquan Wu
Automatic pavement crack detection is crucial for reducing road maintenance costs and ensuring transportation safety. Although convolutional neural networks (CNNs) have been widely used in automatic pavement crack detection, they cannot adequately model ...
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Alexey N. Beskopylny, Evgenii M. Shcherban?, Sergey A. Stel?makh, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Alexey Kozhakin, Diana El?shaeva, Nikita Beskopylny and Gleb Onore
The creation and training of artificial neural networks with a given accuracy makes it possible to identify patterns and hidden relationships between physical and technological parameters in the production of unique building materials, predict mechanical...
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