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Xiaohu Zhang and Haifeng Huang
Crack detection is an important task for road maintenance. Currently, convolutional neural-network-based segmentation models with attention blocks have achieved promising results, for the reason that these models can avoid the interference of lights and ...
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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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Tao Jin, Wen Zhang, Chunlai Chen, Bin Chen, Yizhou Zhuang and He Zhang
Deep-learning- and unmanned aerial vehicle (UAV)-based methods facilitate structural crack detection for tall structures. However, contemporary datasets are generally established using images taken with handheld or vehicle-mounted cameras. Thus, these im...
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Frank Liebold, Franz Wagner, Josiane Giese, Szymon Grzesiak, Christoph de Sousa, Birgit Beckmann, Matthias Pahn, Steffen Marx, Manfred Curbach and Hans-Gerd Maas
Carbon-reinforced concrete (CRC) is increasingly utilized in construction, due to its unique properties, such as corrosion resistance, high-tensile strength, and durability. Understanding its behavior under different loads is crucial to ensuring its safe...
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Yanjie Zhu, Weidong Xu, C. S. Cai and Wen Xiong
After years of service, bridges could lose their expected functions. Considering the significant number of bridges and the adverse inspecting environment, the urgent requirement for timely and efficient inspection solutions, such as computer vision techn...
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Qinge Wu, Zhichao Song, Hu Chen, Yingbo Lu and Lintao Zhou
Crack identification plays a vital role in preventive maintenance strategies during highway pavement maintenance. Therefore, accurate identification of cracks in highway pavement images is the key to highway maintenance work. In this paper, an improved U...
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Kemal Haciefendioglu, Ahmet Can Altunisik and Tugba Abdioglu
The efficient and precise identification of cracks in masonry stone structures caused by natural or human-induced factors within a specific region holds significant importance in detecting damage and subsequent secondary harm. In recent times, remote sen...
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Alessandro Di Benedetto, Margherita Fiani and Lucas Matias Gujski
Many studies on the semantic segmentation of cracks using the machine learning (ML) technique can be found in the relevant literature. To date, the results obtained are quite good, but often the accuracy of the trained model and the results obtained are ...
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Chuan Xu, Qi Zhang, Liye Mei, Xiufeng Chang, Zhaoyi Ye, Junjian Wang, Lang Ye and Wei Yang
Road crack detection is one of the important issues in the field of traffic safety and urban planning. Currently, road damage varies in type and scale, and often has different sizes and depths, making the detection task more challenging. To address this ...
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Esraa Elhariri, Nashwa El-Bendary and Shereen A. Taie
Crack detection on historical surfaces is of significant importance for credible and reliable inspection in heritage structural health monitoring. Thus, several object detection deep learning models are utilized for crack detection. However, the majority...
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