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 critical review and comparative study on image segmentation-based techniques for pavement crack detection
Narges Kheradmandi, Vida Mehranfar
Construction and Building Materials (2022) Vol. 321, pp. 126162-126162
Closed Access | Times Cited: 232

Showing 1-25 of 232 citing articles:

Real-time detection of cracks in tiled sidewalks using YOLO-based method applied to unmanned aerial vehicle (UAV) images
Qiwen Qiu, Denvid Lau
Automation in Construction (2023) Vol. 147, pp. 104745-104745
Closed Access | Times Cited: 113
Review on computer vision-based crack detection and quantification methodologies for civil structures
Jianghua Deng, Amardeep Singh, Yiyi Zhou, et al.
Construction and Building Materials (2022) Vol. 356, pp. 129238-129238
Closed Access | Times Cited: 108
Comparison of histogram-based gradient boosting classification machine, random Forest, and deep convolutional neural network for pavement raveling severity classification
Nhat‐Duc Hoang, Tran Van-Duc
Automation in Construction (2023) Vol. 148, pp. 104767-104767
Closed Access | Times Cited: 61
Image thresholding approaches for medical image segmentation - short literature review
Sandra Jardim, João António, Carlos León de Mora
Procedia Computer Science (2023) Vol. 219, pp. 1485-1492
Open Access | Times Cited: 43
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
Deep learning for surface crack detection in civil engineering: A comprehensive review
Haiyan Zhuang, Yikai Cheng, Man Zhou, et al.
Measurement (2025), pp. 116908-116908
Closed Access | Times Cited: 1
Datasets and processing methods for boosting visual inspection of civil infrastructure: A comprehensive review and algorithm comparison for crack classification, segmentation, and detection
Guidong Yang, Kangcheng Liu, Jihan Zhang, et al.
Construction and Building Materials (2022) Vol. 356, pp. 129226-129226
Closed Access | Times Cited: 51
Combined Use of GPR and Other NDTs for Road Pavement Assessment: An Overview
Ahmed Elseicy, Alex Alonso-Díaz, Mercedes Solla, et al.
Remote Sensing (2022) Vol. 14, Iss. 17, pp. 4336-4336
Open Access | Times Cited: 50
Asphalt pavement fatigue crack severity classification by infrared thermography and deep learning
Fangyu Liu, Jian Liu, Linbing Wang
Automation in Construction (2022) Vol. 143, pp. 104575-104575
Closed Access | Times Cited: 48
Recent computer vision applications for pavement distress and condition assessment
Ayman H. El Hakea, Mohamed Waleed Fakhr
Automation in Construction (2022) Vol. 146, pp. 104664-104664
Closed Access | Times Cited: 39
A novel transformer-based network with attention mechanism for automatic pavement crack detection
Feng Guo, Jian Liu, Chengshun Lv, et al.
Construction and Building Materials (2023) Vol. 391, pp. 131852-131852
Closed Access | Times Cited: 39
Pavement crack detection with hybrid-window attentive vision transformers
Shaozhang Xiao, Kaikai Shang, Ken Lin, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 116, pp. 103172-103172
Open Access | Times Cited: 38
Automatic Pixel-level pavement sealed crack detection using Multi-fusion U-Net network
Jing Shang, Jie Xu, Allen Zhang, et al.
Measurement (2023) Vol. 208, pp. 112475-112475
Closed Access | Times Cited: 37
Revolutionizing concrete analysis: An in-depth survey of AI-powered insights with image-centric approaches on comprehensive quality control, advanced crack detection and concrete property exploration
Kaustav Sarkar, Amit Shiuly, Krishna Gopal Dhal
Construction and Building Materials (2023) Vol. 411, pp. 134212-134212
Closed Access | Times Cited: 34
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: 27
A deep segmentation network for crack detection with progressive and hierarchical context fusion
Lei Yang, Hanyun Huang, Shuyi Kong, et al.
Journal of Building Engineering (2023) Vol. 75, pp. 106886-106886
Closed Access | Times Cited: 25
LCA-YOLOv8-Seg: An Improved Lightweight YOLOv8-Seg for Real-Time Pixel-Level Crack Detection of Dams and Bridges
Yang Wu, Qingbang Han, Qilin Jin, et al.
Applied Sciences (2023) Vol. 13, Iss. 19, pp. 10583-10583
Open Access | Times Cited: 25
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: 21
Multi-stage generative adversarial networks for generating pavement crack images
Chengjia Han, Tao Ma, Ju Huyan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107767-107767
Closed Access | Times Cited: 13
A Multitask Fusion Network for Region-Level and Pixel-Level Pavement Distress Detection
Jingtao Zhong, Miaomiao Zhang, Yuetan Ma, et al.
Journal of Transportation Engineering Part B Pavements (2024) Vol. 150, Iss. 1
Closed Access | Times Cited: 11
Advanced Medical Image Segmentation Enhancement: A Particle-Swarm-Optimization-Based Histogram Equalization Approach
Shoffan Saifullah, Rafał Dreżewski
Applied Sciences (2024) Vol. 14, Iss. 2, pp. 923-923
Open Access | Times Cited: 10
The Crack Diffusion Model: An Innovative Diffusion-Based Method for Pavement Crack Detection
Haoyuan Zhang, Ning Chen, Mei Li, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 986-986
Open Access | Times Cited: 10
CrackDiffusion: A two-stage semantic segmentation framework for pavement crack combining unsupervised and supervised processes
Chengjia Han, Handuo Yang, Tao Ma, et al.
Automation in Construction (2024) Vol. 160, pp. 105332-105332
Closed Access | Times Cited: 9
Automation in road distress detection, diagnosis and treatment
Xu Yang, Jianqi Zhang, Wenbo Liu, et al.
Journal of Road Engineering (2024) Vol. 4, Iss. 1, pp. 1-26
Open Access | Times Cited: 9
An end-to-end computer vision system based on deep learning for pavement distress detection and quantification
Saúl Cano-Ortiz, L. Lloret Iglesias, P. Martínez Ruiz del Árbol, et al.
Construction and Building Materials (2024) Vol. 416, pp. 135036-135036
Open Access | Times Cited: 8
Page 1 - Next Page

Scroll to top