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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A research on an improved Unet-based concrete crack detection algorithm
Lingxin Zhang, Junkai Shen, Baijie Zhu
Structural Health Monitoring (2020) Vol. 20, Iss. 4, pp. 1864-1879
Closed Access | Times Cited: 174

Showing 1-25 of 174 citing articles:

Structural crack detection using deep convolutional neural networks
Ali Raza, Joon Huang Chuah, Mohamad Sofian Abu Talip, et al.
Automation in Construction (2021) Vol. 133, pp. 103989-103989
Closed Access | Times Cited: 235
Efficient attention-based deep encoder and decoder for automatic crack segmentation
Dong Hee Kang, Young‐Jin Cha
Structural Health Monitoring (2021) Vol. 21, Iss. 5, pp. 2190-2205
Open Access | Times Cited: 199
Vision transformer-based autonomous crack detection on asphalt and concrete surfaces
Elyas Asadi Shamsabadi, Chang Xu, Aravinda S. Rao, et al.
Automation in Construction (2022) Vol. 140, pp. 104316-104316
Closed Access | Times Cited: 130
Automatic concrete crack segmentation model based on transformer
Wenjun Wang, Chao Su
Automation in Construction (2022) Vol. 139, pp. 104275-104275
Closed Access | Times Cited: 109
Crack detection using fusion features‐based broad learning system and image processing
Yang Zhang, Ka‐Veng Yuen
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 36, Iss. 12, pp. 1568-1584
Closed Access | Times Cited: 105
Crack detection algorithm for concrete structures based on super-resolution reconstruction and segmentation network
Chaoqun Xiang, Wei Wang, Lu Deng, et al.
Automation in Construction (2022) Vol. 140, pp. 104346-104346
Closed Access | Times Cited: 77
Mutual information based anomaly detection of monitoring data with attention mechanism and residual learning
Xiaoming Lei, Ye Xia, Ao Wang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 182, pp. 109607-109607
Closed Access | Times Cited: 71
Automatic Damage Detection and Diagnosis for Hydraulic Structures Using Drones and Artificial Intelligence Techniques
Yantao Zhu, Hongwu Tang
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 615-615
Open Access | Times Cited: 64
Computer Vision-Based Bridge Inspection and Monitoring: A Review
Kui Luo, Xuan Kong, Jie Zhang, et al.
Sensors (2023) Vol. 23, Iss. 18, pp. 7863-7863
Open Access | Times Cited: 54
Lightweight semantic segmentation of complex structural damage recognition for actual bridges
Yang Xu, Yunlei Fan, Hui Li
Structural Health Monitoring (2023) Vol. 22, Iss. 5, pp. 3250-3269
Closed Access | Times Cited: 48
CrackSeg9k: A Collection and Benchmark for Crack Segmentation Datasets and Frameworks
Shreyas Kulkarni, Shreyas Singh, Dhananjay Balakrishnan, et al.
Lecture notes in computer science (2023), pp. 179-195
Closed Access | Times Cited: 42
Task-aware meta-learning paradigm for universal structural damage segmentation using limited images
Yang Xu, Yunlei Fan, Yuequan Bao, et al.
Engineering Structures (2023) Vol. 284, pp. 115917-115917
Closed Access | Times Cited: 41
CNN-Transformer hybrid network for concrete dam crack patrol inspection
Mingchao Li, Jingyue Yuan, Qiubing Ren, et al.
Automation in Construction (2024) Vol. 163, pp. 105440-105440
Closed Access | Times Cited: 18
Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning
Yangtao Li, Tengfei Bao, Xianjun Huang, et al.
Automation in Construction (2022) Vol. 144, pp. 104600-104600
Closed Access | Times Cited: 62
Deep learning-based crack segmentation for civil infrastructure: data types, architectures, and benchmarked performance
Shanglian Zhou, Carlos Canchila, Wei Song
Automation in Construction (2022) Vol. 146, pp. 104678-104678
Closed Access | Times Cited: 60
A review of the research and application of deep learning-based computer vision in structural damage detection
Lingxin Zhang, Junkai Shen, Zhu Baijie
Earthquake Engineering and Engineering Vibration (2022) Vol. 21, Iss. 1, pp. 1-21
Closed Access | Times Cited: 58
Pixel-level road crack detection in UAV remote sensing images based on ARD-Unet
Yuxi Gao, Hongbin Cao, Weiwei Cai, et al.
Measurement (2023) Vol. 219, pp. 113252-113252
Closed Access | Times Cited: 40
Modeling automatic pavement crack object detection and pixel-level segmentation
Yuchuan Du, Shan Zhong, Hongyuan Fang, et al.
Automation in Construction (2023) Vol. 150, pp. 104840-104840
Closed Access | Times Cited: 37
High-resolution concrete damage image synthesis using conditional generative adversarial network
Shengyuan Li, Xuefeng Zhao
Automation in Construction (2023) Vol. 147, pp. 104739-104739
Closed Access | Times Cited: 35
Semi-supervised learning framework for crack segmentation based on contrastive learning and cross pseudo supervision
Chaoqun Xiang, Vincent J.L. Gan, Guo Jingjing, et al.
Measurement (2023) Vol. 217, pp. 113091-113091
Closed Access | Times Cited: 32
Establishment and evaluation of conditional GAN-based image dataset for semantic segmentation of structural cracks
Tao Jin, Xiao‐Wei Ye, Zecheng Li
Engineering Structures (2023) Vol. 285, pp. 116058-116058
Closed Access | Times Cited: 28
Image Processing Techniques for Concrete Crack Detection: A Scientometrics Literature Review
Md. Al-Masrur Khan, Seong‐Hoon Kee, Al‐Sakib Khan Pathan, et al.
Remote Sensing (2023) Vol. 15, Iss. 9, pp. 2400-2400
Open Access | Times Cited: 28
Deep Learning for Structural Health Monitoring: Data, Algorithms, Applications, Challenges, and Trends
Jing Jia, Ying Li
Sensors (2023) Vol. 23, Iss. 21, pp. 8824-8824
Open Access | Times Cited: 28
A deep learning semantic segmentation network with attention mechanism for concrete crack detection
Jiaqi Hang, Yingjie Wu, Yancheng Li, et al.
Structural Health Monitoring (2023) Vol. 22, Iss. 5, pp. 3006-3026
Closed Access | Times Cited: 27
Automated building layout generation using deep learning and graph algorithms
Lufeng Wang, Jiepeng Liu, Zeng Yan, et al.
Automation in Construction (2023) Vol. 154, pp. 105036-105036
Closed Access | Times Cited: 27
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