Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 sigmoid‐optimized encoder–decoder network for crack segmentation with copy‐edit‐paste transfer learning
Firdes Çelik, Markus König
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 37, Iss. 14, pp. 1875-1890
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network
Zhong Zhou, Junjie Zhang, Chenjie Gong
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 38, Iss. 17, pp. 2491-2510
Open Access | Times Cited: 97
Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
Torkan Shafighfard, Farzin Kazemi, Faramarz Bagherzadeh, et al.
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 23, pp. 3573-3594
Open Access | Times Cited: 53
A lightweight encoder–decoder network for automatic pavement crack detection
Guijie Zhu, Jiacheng Liu, Zhun Fan, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 12, pp. 1743-1765
Open Access | Times Cited: 42
Real‐time automatic crack detection method based on drone
Shiqiao Meng, Zhiyuan Gao, Ying Zhou, et al.
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 38, Iss. 7, pp. 849-872
Closed Access | Times Cited: 64
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: 62
A graph‐based method for quantifying crack patterns on reinforced concrete shear walls
Pedram Bazrafshan, Thinh On, Sina Basereh, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 4, pp. 498-517
Closed Access | Times Cited: 29
Deep learning algorithm for real-time automatic crack detection, segmentation, qualification
Gang Xu, Qingrui Yue, Xiaogang Liu
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107085-107085
Closed Access | Times Cited: 28
A lightweight crack segmentation network based on knowledge distillation
Wenjun Wang, Chao Su, Guohui Han, et al.
Journal of Building Engineering (2023) Vol. 76, pp. 107200-107200
Closed Access | Times Cited: 26
Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network
Hong-Hu Chu, Pang-jo CHUN
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 4, pp. 575-594
Open Access | Times Cited: 24
Real-time monitoring of concrete crack based on deep learning algorithms and image processing techniques
Gang Xu, Qingrui Yue, Xiaogang Liu
Advanced Engineering Informatics (2023) Vol. 58, pp. 102214-102214
Closed Access | Times Cited: 23
Self‐training with Bayesian neural networks and spatial priors for unsupervised domain adaptation in crack segmentation
Pang-jo CHUN, T. Kikuta
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 17, pp. 2642-2661
Open Access | Times Cited: 13
A lightweight feature attention fusion network for pavement crack segmentation
Yucheng Huang, Yuchen Liu, Fang Liu, et al.
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 18, pp. 2811-2825
Open Access | Times Cited: 8
Semi-supervised semantic image segmentation by deep diffusion models and generative adversarial networks
José Ángel Díaz-Francés, José David Fernández-Rodríguez, Karl Thurnhofer‐Hemsi, et al.
International Journal of Neural Systems (2024) Vol. 34, Iss. 11
Closed Access | Times Cited: 8
Methodology to integrate augmented reality and pattern recognition for crack detection
Kaveh Malek, Ali Mohammadkhorasani, Fernando Moreu
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 38, Iss. 8, pp. 1000-1019
Closed Access | Times Cited: 27
An optimized and precise road crack segmentation network in complex scenarios
Gang Wang, Mingfang He, Genhua Liu, et al.
Computer-Aided Civil and Infrastructure Engineering (2025)
Closed Access
Quantitative road crack evaluation by a U‐Net architecture using smartphone images and Lidar data
Takahiro Yamaguchi, Tsukasa Mizutani
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 7, pp. 963-982
Open Access | Times Cited: 12
Road crack detection interpreting background images by convolutional neural networks and a self‐organizing map
Takahiro Yamaguchi, Tsukasa Mizutani
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 11, pp. 1616-1640
Open Access | Times Cited: 12
Learning monocular depth estimation for defect measurement from civil RGB-D dataset
Max Midwinter, Zaid Abbas Al‐Sabbag, Rishabh Bajaj, et al.
Structural Health Monitoring (2025)
Closed Access
Generative adversarial network based on domain adaptation for crack segmentation in shadow environments
Yingchao Zhang, Cheng Liu
Computer-Aided Civil and Infrastructure Engineering (2025)
Open Access
Implicit function‐based continuous representation for meticulous segmentation of cracks from high‐resolution images
Hong-Hu Chu, Lizhi Long, Jingjing Guo, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 4, pp. 539-558
Closed Access | Times Cited: 10
Unsupervised defect segmentation with pose priors
Max Midwinter, Zaid Abbas Al‐Sabbag, Chul Min Yeum
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 38, Iss. 17, pp. 2455-2471
Open Access | Times Cited: 8
Efficient data dimensionality reduction method for improving road crack classification algorithms
Francisco J. Rodriguez‐Lozano, Juan Carlos Valenzuela Gámez, José M. Palomares, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 38, Iss. 16, pp. 2339-2354
Open Access | Times Cited: 7
TwinGen: Advanced technologies to automatically generate digital twins for operation and maintenance of existing bridges
Simon Vilgertshofer, M. S. Mafipour, A. Borrmann, et al.
CRC Press eBooks (2023), pp. 213-220
Open Access | Times Cited: 6
Digital twinning of bridges from point cloud data by deep learning and parametric models
M. Saeed Mafipour, Simon Vilgertshofer, A. Borrmann
CRC Press eBooks (2023), pp. 543-550
Open Access | Times Cited: 5
Fully decouple convolutional network for damage detection of rebars in RC beams
Haowei Zhang, Kang Gao, Huiying Huang, et al.
Engineering Structures (2023) Vol. 285, pp. 116023-116023
Closed Access | Times Cited: 5
Page 1 - Next Page

Scroll to top