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 transformer and self-cascade operation-based architecture for segmenting high-resolution bridge cracks
Hong-Hu Chu, Lu Deng, Huaqing Yuan, et al.
Automation in Construction (2023) Vol. 158, pp. 105194-105194
Closed Access | Times Cited: 12

Showing 12 citing articles:

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
Research on Energy Efficiency Evaluation System for Rural Houses Based on Improved Mask R-CNN Network
Liping He, K. Gao, Yuan Jin, et al.
Sustainability (2025) Vol. 17, Iss. 3, pp. 1132-1132
Open Access
Weak feature crack detection in high-resolution concrete dam surface image with LarkMNet
Jianyuan Li, Xiaochun Lu, Ping Zhang, et al.
Measurement (2024) Vol. 238, pp. 115327-115327
Open Access | Times Cited: 3
Enhancing pixel-level crack segmentation with visual mamba and convolutional networks
Chengjia Han, Handuo Yang, Yaowen Yang
Automation in Construction (2024) Vol. 168, pp. 105770-105770
Closed Access | Times Cited: 3
Deep learning-based method for detection and feature quantification of microscopic cracks on the surface of concrete dams
Xiaochun Lu, Qingquan Li, Jianyuan Li, et al.
Measurement (2024) Vol. 240, pp. 115587-115587
Closed Access | Times Cited: 2
A non-local based microcrack segmentation model optimized for effective high resolution and low-power devices
Kyungsu Kang, JoonOh Seo, Han-Guk Ryu
Journal of Building Engineering (2024) Vol. 96, pp. 110650-110650
Closed Access | Times Cited: 1
Automatic assessment of concrete cracks in low-light, overexposed, and blurred images restored using a generative AI approach
Pengwei Guo, Xiangjun Meng, Weina Meng, et al.
Automation in Construction (2024) Vol. 168, pp. 105787-105787
Closed Access | Times Cited: 1
Real-time spatial contextual network based on deep learning for bridge exposed rebar segmentation
Yong Wang, Zhenglong He, Xiangqiang Zeng, et al.
Construction and Building Materials (2024) Vol. 449, pp. 138379-138379
Closed Access | Times Cited: 1
Quantitative assessment of cracks in concrete structures using active-learning-integrated transformer and unmanned robotic platform
Wei Ding, Jiangpeng Shu, Carl J. Debono, et al.
Automation in Construction (2024) Vol. 168, pp. 105829-105829
Closed Access | Times Cited: 1
Semantics-Enhanced Refiner in Skip Connection for Crack Segmentation
Zhigao Zeng, Jin Wang, Cao Wei, et al.
Lecture notes in computer science (2024), pp. 81-92
Closed Access
Surface fatigue crack segmentation in steel box girder bridges using an improved Unet convolutional neural network
Tian Gao, Zhiyuan Yuanzhou, Bohai Ji, et al.
Structure and Infrastructure Engineering (2024), pp. 1-12
Closed Access
Enhancing bridge damage detection with Mamba-Enhanced HRNet for semantic segmentation
Jie Liu, D. Li, Xinyue Xu
PLoS ONE (2024) Vol. 19, Iss. 10, pp. e0312136-e0312136
Open Access
Page 1

Scroll to top