You Only Look Once v5 and Multi-Template Matching for Small-Crack Defect Detection on Metal Surfaces by Pallavi Dubey, Seth Miller, Elif Elçin Günay, John Jackman, Gül E. Kremer, Paul A. Kremer

“…This study used You Only Look Once v5 (YOLOv5) as the DL model and compared its performance against the MTM model for small-crack detection. The findings of our preliminary investigation are as follows: (i) YOLOv5 demonstrated higher performance than MTM in detecting small cracks; (ii) an extra-large variant of YOLOv5 outperformed a small-size variant; (iii) the size and object variety of the data are crucial in achieving robust pre-trained weights for use in transfer learning; and (iv) enhanced image resolution contributes to precise object detection.…”
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Detection of Flexible Pavement Surface Cracks in Coastal Regions Using Deep Learning and 2D/3D Images by Carlos Sanchez, Feng Wang, Yongsheng Bai, Haitao Gong

“…Along with emphasis on efforts to detect cracks in the presence of background noise on asphalt pavements, six scenarios for augmentation were made to evaluate the model’s performance based on flip probability in the horizontal and vertical directions. …”
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Crack Detection in Civil Infrastructure Using Autonomous Robotic Systems: A Synergistic Review of Platforms, Cognition, and Autonomous Action by Rong Dai, Rui Wang, Chang Shu, Jianming Li, Zhe Wei

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Evaluation of the possibility of detecting cracks during the control of luminescence on turbine blades after application of complex heat-resistant coatings by Konstantin Balushok, Oleksandr Seliverstov, Oleksandr Prokopenko, Sergii Sakhno

“…The paper evaluates the possibility of detecting cracks on GTD turbine blades with complex heat-resistant coatings GCP+SDP-2. …”
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Optimizing deep belief network for concrete crack detection via a modified design of ideal gas molecular dynamics by Tan Qin, Gongxing Yan, Huaguo Jiang, Minqi Shen, Andrea Settanni

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A probabilistic fatigue crack growth life approach to the definition of inspection intervals for railway axles by C. Mallor, S. Calvo, J.L. N��ez, R. Rodr�guez-Barrachina, A. Landaberea CAF S.A., J.M. Iturrioz, 26, Beasain, Gipuzkoa, Spain

Subjects: “…probabilistic fatigue crack growth…”
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CrackNet: A Hybrid Model for Crack Segmentation with Dynamic Loss Function by Yawen Fan, Zhengkai Hu, Qinxin Li, Yang Sun, Jianxin Chen, Quan Zhou

“…Along with the development of deep learning, visual-based crack automatic detection has been widely studied. …”
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Crack Detection, Classification, and Segmentation on Road Pavement Material Using Multi-Scale Feature Aggregation and Transformer-Based Attention Mechanisms by Arselan Ashraf, Ali Sophian, Ali Aryo Bawono

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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process by Akshansh Mishra, Vijaykumar S. Jatti, Nitin K. Khedkar, Rahul B. Dhabale, Ashwini V. Jatti

“…The results showed that the fracture cracks can be validated by testing with higher accuracy. …”
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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process by Akshansh Mishra, Vijaykumar S Jatti, Nitin K Khedkar, Rahul B. Dhabale, Ashwini V Jatti

“…The results showed that the fracture cracks can be validated by testing with higher accuracy. …”
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Analysis of Acoustic Emission Waveforms by Wavelet Packet Transform for the Detection of Crack Initiation Due to Fretting Fatigue in Solid Railway Axles by Marta Zamorano, María Jesús Gómez, Cristina Castejon, Michele Carboni

“…One of the most subtle damage mechanisms affecting these components is fretting fatigue, which is a particularly challenging damage mechanism in these components, as it can initiate cracks under real service conditions and is difficult to detect in its early stages, which is vital to ensure operational safety and to optimize maintenance strategies. …”
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Binocular Video-Based Automatic Pixel-Level Crack Detection and Quantification Using Deep Convolutional Neural Networks for Concrete Structures by Liqu Liu, Bo Shen, Shuchen Huang, Runlin Liu, Weizhang Liao, Bin Wang, Shuo Diao

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Automated Crack Width Measurement in 3D Models: A Photogrammetric Approach with Image Selection by Huseyin Yasin Ozturk, Emanuele Zappa

Subjects: “…crack detection…”
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Crack-ConvT Net: A Convolutional Transformer Network for Crack Segmentation in Underwater Dams by Pengfei Shi, Hongzhu Chen, Zaiming Geng, Xinnan Fan, Yuanxue Xin

“…Abstract Crack detection is a critical approach to ensuring the structural health of dams. …”
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Enhance the Concrete Crack Classification Based on a Novel Multi-Stage YOLOV10-ViT Framework by Ali Mahmoud Mayya, Nizar Faisal Alkayem

Subjects: “…crack detection…”
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Assessing crack formation and strain distribution in concrete structures using externally installed fiber optic sensors by Henrik Becks, Matthias Högemann, Josef Hegger, Martin Classen

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A Quasi-Distributed Crack Sensor Based on Weakly Coupled Vertical U-Shaped Ring Array by Chenjie Chu, Jiayi Huang, Xuan Xie, Jun Zhang

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Characterizing the Cracking Behavior of Large-Scale Multi-Layered Reinforced Concrete Beams by Acoustic Emission Analysis by Yara A. Zaki, Ahmed A. Abouhussien, Assem A. A. Hassan

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LiDAR-Based Road Cracking Detection: Machine Learning Comparison, Intensity Normalization, and Open-Source WebGIS for Infrastructure Maintenance by Nicole Pascucci, Donatella Dominici, Ayman Habib

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Metaheuristic Optimized Edge Detection for Recognition of Concrete Wall Cracks: A Comparative Study on the Performances of Roberts, Prewitt, Canny, and Sobel Algorithms by Nhat-Duc Hoang, Quoc-Lam Nguyen

“…Crack detection is a crucial task in the periodic survey of high-rise buildings and infrastructure. …”
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