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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:

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

Showing 1-25 of 42 citing articles:

Automated crack detection and mapping of bridge decks using deep learning and drones
Da Hu, Tien Yee, Dale Goff
Journal of Civil Structural Health Monitoring (2024) Vol. 14, Iss. 3, pp. 729-743
Closed Access | Times Cited: 10
Deep learning-assisted automatic quality assessment of concrete surfaces with cracks and bugholes
Jiepeng Liu, Zhengtao Yang, Hongtuo Qi, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102577-102577
Closed Access | Times Cited: 7
Efficient hybrid ensembles of CNNs and transfer learning models for bridge deck image-based crack detection
Ali Mayya, Nizar Faisal Alkayem, Lei Shen, et al.
Structures (2024) Vol. 64, pp. 106538-106538
Closed Access | Times Cited: 7
Pixel-level concrete bridge crack detection using Convolutional Neural Networks, gabor filters, and attention mechanisms
Hajar Zoubir, Mustapha Rguig, Mohamed El Aroussi, et al.
Engineering Structures (2024) Vol. 314, pp. 118343-118343
Closed Access | Times Cited: 7
From classification to segmentation with explainable AI: A study on crack detection and growth monitoring
Florent Forest, Hugo Porta, Devis Tuia, et al.
Automation in Construction (2024) Vol. 165, pp. 105497-105497
Open Access | Times Cited: 6
A controllable generative model for generating pavement crack images in complex scenes
Hancheng Zhang, Zhendong Qian, Wei Zhou, et al.
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 12, pp. 1795-1810
Open Access | Times Cited: 5
dacl10k: Benchmark for Semantic Bridge Damage Segmentation
Johannes Flotzinger, Philipp J. Rösch, Thomas Braml
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2024), pp. 8611-8620
Open Access | Times Cited: 5
Robotic inspection for autonomous crack segmentation and exploration using deep reinforcement learning
chengxiang fan, Rih‐Teng Wu, Yung-I Chang
Automation in Construction (2025), pp. 106009-106009
Closed Access
Vector-Quantized Variational Teacher and Multimodal Collaborative Student for Crack Segmentation via Knowledge Distillation
Shi Qiu, Qasim Zaheer, Syed Muhammad Ahmed Hassan Shah, et al.
Journal of Computing in Civil Engineering (2025) Vol. 39, Iss. 3
Closed Access
BBCNet: Boundary-Body Coherence Network with Adaptive Self-Attention Distillation for Enhanced Crack Segmentation
Xiao Hu, Kang Liu, Zhihao Xv
Digital Signal Processing (2025), pp. 105148-105148
Closed Access
ISTD-CrackNet: Hybrid CNN-transformer models focusing on fine-grained segmentation of multi-scale pavement cracks
Zaiyan Zhang, Yangyang Zhuang, Song Wei-dong, et al.
Measurement (2025), pp. 117215-117215
Closed Access
Learning Structure for Concrete Crack Detection Using Robust Super-Resolution with Generative Adversarial Network
Jin Kim, Seungbo Shim, Seok-Jun Kang, et al.
Structural Control and Health Monitoring (2023) Vol. 2023, pp. 1-16
Open Access | Times Cited: 11
Local–Global Feature Adaptive Fusion Network for Building Crack Detection
Yibin He, Zhiqiang Yuan, Xin Xia, et al.
Sensors (2024) Vol. 24, Iss. 21, pp. 7076-7076
Open Access | Times Cited: 4
PCTC-Net: A Crack Segmentation Network with Parallel Dual Encoder Network Fusing Pre-Conv-Based Transformers and Convolutional Neural Networks
Jihwan Moon, Gyu Ho Choi, Yu-Hwan Kim, et al.
Sensors (2024) Vol. 24, Iss. 5, pp. 1467-1467
Open Access | Times Cited: 3
CrackNex: a Few-shot Low-light Crack Segmentation Model Based on Retinex Theory for UAV Inspections
Zhen Yao, Jiawei Xu, Shuhang Hou, et al.
(2024), pp. 11155-11162
Open Access | Times Cited: 3
Mind marginal non-crack regions: Clustering-inspired representation learning for crack segmentation
Zhuangzhuang Chen, Zhuonan Lai, Jie Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 32, pp. 12698-12708
Closed Access | Times Cited: 3
Hybrid-Segmentor: A Hybrid Approach to Automated Damage Detection on Civil Infrastructure
June Moh Goo, Xenios Milidonis, Alessandro Artusi, et al.
(2024)
Open Access | Times Cited: 2
Rs-net: Residual Sharp U-Net architecture for pavement crack segmentation and severity assessment
Luqman Ali, Hamad Al Jassmi, Mohammed Swavaf, et al.
Journal Of Big Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Co-CrackSegment: A New Corporative Deep Learning Framework for Pixel-Level Semantic Segmentation of Concrete Cracks
Nizar Faisal Alkayem, Ali Mayya, Xin Zhang, et al.
(2024)
Open Access | Times Cited: 2
dacl-challenge: Semantic Segmentation during Visual Bridge Inspections
Johannes Flotzinger, Philipp J. Rösch, Christian Benz, et al.
(2024), pp. 716-725
Closed Access | Times Cited: 1
Automated Pavement Distress Detection Based on Convolutional Neural Network
Jinhe Zhang, Shangyu Sun, Weidong Song, et al.
IEEE Access (2024) Vol. 12, pp. 105055-105068
Open Access | Times Cited: 1
CrackScopeNet: A Lightweight Neural Network for Rapid Cracks Detection on Resource-Constrained Drone Platforms
Tao Zhang, Liwei Qin, Quan Zou, et al.
(2024)
Open Access | Times Cited: 1
CrackScopeNet: A Lightweight Neural Network for Rapid Cracks Detection on Resource-Constrained Drone Platforms
Tao Zhang, Liwei Qin, Quan Zou, et al.
(2024)
Open Access | Times Cited: 1
Real-Time ConvNext-Based U-Net with Feature Infusion for Egg Microcrack Detection
Chenbo Shi, Yuejia Li, Xin Jiang, et al.
Agriculture (2024) Vol. 14, Iss. 9, pp. 1655-1655
Open Access | Times Cited: 1
E3-Net: Event-Guided Edge-Enhancement Network for UAV-based Crack Detection
Ran Duan, Bo Wu, Hao Zhou, et al.
2022 International Conference on Advanced Robotics and Mechatronics (ICARM) (2024), pp. 272-277
Closed Access | Times Cited: 1
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