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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:

DeepCrackAT: An effective crack segmentation framework based on learning multi-scale crack features
Qinghua Lin, Wei Li, Xiangpan Zheng, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106876-106876
Closed Access | Times Cited: 24

Showing 24 citing articles:

Visual Concrete Bridge Defect Classification and Detection Using Deep Learning: A Systematic Review
Dariush Amirkhani, Mohand Saïd Allili, Loucif Hebbache, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 9, pp. 10483-10505
Closed Access | Times Cited: 10
CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer
Kai Liu, Tao Ren, Zhangli Lan, et al.
Buildings (2025) Vol. 15, Iss. 2, pp. 197-197
Open Access | Times Cited: 1
A multiscale enhanced pavement crack segmentation network coupling spectral and spatial information of UAV hyperspectral imagery
Xiao Chen, Xianfeng Zhang, Miao Ren, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 128, pp. 103772-103772
Open Access | Times Cited: 4
Unified weakly and semi-supervised crack segmentation framework using limited coarse labels
Chao Xiang, Vincent J.L. Gan, Lu Deng, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108497-108497
Closed Access | Times Cited: 4
Efficient surface crack segmentation for industrial and civil applications based on an enhanced YOLOv8 model
Zeinab F. Elsharkawy, H. Kasban, Mohammed Y. Abbass
Journal Of Big Data (2025) Vol. 12, Iss. 1
Open Access
A Novel Measuring Method for Drop Strength of Green Pellets Using Machine Vision
Shuyi Zhou, Xiaoyan Liu, Fei Li
(2025)
Closed Access
DCMA-Net: A dual channel multi-scale feature attention network for crack image segmentation
Yidan Yan, Junding Sun, Hongyuan Zhang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110411-110411
Closed Access
Phased Noise Enhanced Multiple Feature Discrimination Network for fabric defect detection
Haoran Ma, Zuoyong Li, Haoyi Fan, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110480-110480
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
Segmentation refinement of thin cracks with Minimum Strip Cuts
Wanchen Hou, Jingyuan He, Chenghao Cui, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103249-103249
Closed Access
Visual-Based Deep Convolutional Neural Network Method for Detecting Damage in Bridge Plate Rubber Bearings
Yongkang Chen, Weirong Li, Guangjun Sun, et al.
Transportation Research Record Journal of the Transportation Research Board (2025)
Closed Access
A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation
Yuhang Zhu, Zhezhuang Xu, Ye Lin, et al.
Sensors (2024) Vol. 24, Iss. 5, pp. 1635-1635
Open Access | Times Cited: 3
Classification of battery laser welding defects via enhanced image preprocessing methods and explainable artificial intelligence-based verification
Sujin Hwang, Jongsoo Lee
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108311-108311
Closed Access | Times Cited: 3
EAFNet: Extraction-amplification-fusion network for tiny cracks detection
Z. Zhou, Wensong Zhao, Kechen Song, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108691-108691
Closed Access | Times Cited: 2
CrackScopeNet: A Lightweight Neural Network for Rapid Crack Detection on Resource-Constrained Drone Platforms
Tao Zhang, Liwei Qin, Quan Zou, et al.
Drones (2024) Vol. 8, Iss. 9, pp. 417-417
Open Access | Times Cited: 1
A novel convolutional neural network for enhancing the continuity of pavement crack detection
Jinhe Zhang, Shangyu Sun, Song Wei-dong, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
UTE-CrackNet: transformer-guided and edge feature extraction U-shaped road crack image segmentation
Huaping Zhou, Bin Deng, Kelei Sun, et al.
The Visual Computer (2024)
Closed 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
MixSegNet: A Novel Crack Segmentation Network Combining CNN and Transformer
Yang Zhou, Ali Raza, Norrima Mokhtar, et al.
IEEE Access (2024) Vol. 12, pp. 111535-111545
Open Access
ASCL: Accelerating semi‐supervised learning via contrastive learning
Liu Hai-xiong, Zuoyong Li, Jiawei Wu, et al.
Concurrency and Computation Practice and Experience (2024) Vol. 36, Iss. 28
Open Access
Dual-encoder network for pavement concrete crack segmentation with multi-stage supervision
Jing Wang, Hong Liang Yao, Jinbin Hu, et al.
Automation in Construction (2024) Vol. 169, pp. 105884-105884
Closed Access
RepCrack: An efficient pavement crack segmentation method based on structural re-parameterization
Mingcheng Ni, Lei Chen, Peixin Shi, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 141, pp. 109791-109791
Closed Access
TSPCS-net: Two-stage pavement crack segmentation network based on encoder-decoder architecture
Biao Yue, Jianwu Dang, Qi Sun, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 141, pp. 109840-109840
Closed Access
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