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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:

Weakly supervised pavement crack semantic segmentation based on multi-scale object localization and incremental annotation refinement
Zaid Al‐Huda, Bo Peng, Riyadh Nazar Ali Algburi, et al.
Applied Intelligence (2022) Vol. 53, Iss. 11, pp. 14527-14546
Closed Access | Times Cited: 23

Showing 23 citing articles:

A hybrid deep learning pavement crack semantic segmentation
Zaid Al‐Huda, Bo Peng, Riyadh Nazar Ali Algburi, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 122, pp. 106142-106142
Closed Access | Times Cited: 68
Semi-supervised learning framework for crack segmentation based on contrastive learning and cross pseudo supervision
Chaoqun Xiang, Vincent J.L. Gan, Guo Jingjing, et al.
Measurement (2023) Vol. 217, pp. 113091-113091
Closed Access | Times Cited: 32
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 | Times Cited: 1
SelectSeg: Uncertainty-based selective training and prediction for accurate crack segmentation under limited data and noisy annotations
Chen Zhang, Mahdi Bahrami, Dhanada K. Mishra, et al.
Reliability Engineering & System Safety (2025), pp. 110909-110909
Closed Access | Times Cited: 1
Asymmetric dual-decoder-U-Net for pavement crack semantic segmentation
Zaid Al‐Huda, Bo Peng, Riyadh Nazar Ali Algburi, et al.
Automation in Construction (2023) Vol. 156, pp. 105138-105138
Closed Access | Times Cited: 19
One-stop multiscale reconciliation attention network with scribble supervision for salient object detection in optical remote sensing images
Ruixiang Yan, Longquan Yan, Yufei Cao, et al.
Applied Intelligence (2024) Vol. 54, Iss. 5, pp. 3737-3755
Closed Access | Times Cited: 5
A review of crack research in concrete structures based on data-driven and intelligent algorithms
Congcong Fan, Youliang Ding, Xujia Liu, et al.
Structures (2025) Vol. 75, pp. 108800-108800
Closed Access
A three-stage pavement image crack detection framework with positive sample augmentation
Qingsong Song, Li Liu, Na Lü, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107624-107624
Closed Access | Times Cited: 12
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
Research on Weakly Supervised Pavement Crack Segmentation Based on Defect Location by Generative Adversarial Network and Target Re‐optimization
Tiejun He, Huaen Li, Zhendong Qian, et al.
Construction and Building Materials (2023) Vol. 411, pp. 134668-134668
Closed Access | Times Cited: 7
Annotate less but perform better: weakly supervised shadow detection via label augmentation
Hongyu Chen, Xiao-Diao Chen, Wen Wu, et al.
The Visual Computer (2024) Vol. 40, Iss. 10, pp. 6763-6777
Closed Access | Times Cited: 2
Lightweight decoder U-net crack segmentation network based on depthwise separable convolution
Yongbo Yu, Yage Zhang, Junyang Yu, et al.
Multimedia Systems (2024) Vol. 30, Iss. 5
Closed Access | Times Cited: 2
End-to-end semi-supervised deep learning model for surface crack detection of infrastructures
Mohammed Ameen Mohammed, Zheng Han, Yange Li, et al.
Frontiers in Materials (2022) Vol. 9
Open Access | Times Cited: 8
A weakly-supervised deep learning model for end-to-end detection of airfield pavement distress
Zefeng Tao, Hongren Gong, Li Liu, et al.
International Journal of Transportation Science and Technology (2024)
Open Access | Times Cited: 1
Parallel desires: unifying local and semantic feature representations in marine species images for classification
Dhana Lakshmi Manikandan, Sakthivel Murugan Santhanam
Marine Geophysical Research (2024) Vol. 45, Iss. 3
Closed Access | Times Cited: 1
SS-CCDN: A semi-supervised pixel-wise concrete crack detection network using multi-task learning and memory information
Xiaobo Zhang, Haihao Tang, Chuanjin Yu, et al.
Measurement (2024) Vol. 239, pp. 115478-115478
Closed Access | Times Cited: 1
Polarized Attention Weak Supervised Semantic Segmentation Network
Min Dai, D.-B. Wu, Yang Dawei
IEEE Access (2024) Vol. 12, pp. 53965-53973
Open Access
Images Data Set Improvement Using Mathematical Morphology Operators
Dumitru Abrudan, Ioana Marcu, Ana–Maria Drăgulinescu, et al.
(2024), pp. 450-455
Closed Access
An end-to-end repair-based joint training framework for weakly supervised pavement crack segmentation
Hui Zhou, Huanjie Tao, Qianyue Duan, et al.
Multimedia Tools and Applications (2024)
Closed Access
Triplet Attention-Enhanced UNet Architectures for Advanced Skin Lesion Segmentation
Zaid Al‐Huda, Mugahed A. Al-antari, Riyadh Nazar Ali Algburi, et al.
(2024), pp. 1-8
Closed Access
Harmonizing Output Imbalance for Defect Segmentation on Extremely-Imbalanced Monocrystalline Solar Cell Images
Jianye Yi, Xiaopin Zhong, Weixiang Liu, et al.
(2024)
Closed Access
CAC: Confidence-Aware Co-Training for Weakly Supervised Crack Segmentation
Fengjiao Liang, Qingyong Li, Xiaobao Li, et al.
Entropy (2024) Vol. 26, Iss. 4, pp. 328-328
Open Access
Hierarchical Multi-scale Visual Attention Module for Wall Putty Bulge Terminals Detection
Mahmoud A. Eldosoky, Jianping Li, Amin Ul Haq, et al.
(2023), pp. 638-643
Closed Access | Times Cited: 1
MDAU-Net: A Multi-Scale U-Net with Dual Attention Module for Pavement Crack Segmentation
Zaid Al‐Huda, Bo Peng, Mugahed A. Al-antari, et al.
2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) (2023), pp. 170-177
Closed Access | Times Cited: 1
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