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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:

A Novel Weld Defect Detection Method for Intelligent Magnetic Flux Leakage Detection System via Contextual Relation Network
Xiangkai Shen, Jinhai Liu, Lin Jiang, et al.
IEEE Transactions on Industrial Electronics (2023) Vol. 71, Iss. 6, pp. 6304-6314
Closed Access | Times Cited: 11

Showing 11 citing articles:

Design and Study of EMAT-MFL Based Hybrid Sensor for Defect Detection in Ferromagnetic Materials
Jie Yuan, Zhen Wang, Mengqi Yuan, et al.
IEEE Transactions on Instrumentation and Measurement (2025) Vol. 74, pp. 1-8
Closed Access
Quantitative Assessment of Pipeline Defects Utilizing a Dual-Stage Deep Learning Framework: Integration of Pretrained YOLO Network and Multi-input Parallel Convolution Architectures on Magnetic Flux Leakage Data
Jialiang Xie, Jie Yang, Kuan Fu, et al.
Journal of Pipeline Science and Engineering (2025), pp. 100282-100282
Open Access
Irregular Defect Size Estimation for the Magnetic Flux Leakage Detection System via Expertise-Informed Collaborative Network
Lei Wang, Huaguang Zhang, Jinhai Liu, et al.
IEEE Transactions on Industrial Electronics (2024) Vol. 71, Iss. 10, pp. 13189-13200
Closed Access | Times Cited: 1
Low-contrast X-ray image defect segmentation via a novel core-profile decomposition network
Xiaoyuan Liu, Jinhai Liu, Huanqun Zhang, et al.
Computers in Industry (2024) Vol. 161, pp. 104123-104123
Closed Access
A multimodal deep learning method of weld defect detection based on 3D point cloud
Kaiyuan Lin, Fang Li, Jiacheng Huang, et al.
Research Square (Research Square) (2024)
Open Access
MSIDetector: Detecting Multi-Scenario industrial defects using an adapted visual foundation model and dual thresholding discriminator
Xujie He, Jing Jin, Fujiang Yu, et al.
Measurement (2024), pp. 115753-115753
Closed Access
A novel anomaly detection method for magnetic flux leakage signals via a feature-based unsupervised detection network
He Zhao, Jinhai Liu, Qiannan Wang, et al.
Computers in Industry (2024) Vol. 164, pp. 104190-104190
Closed Access
A Surface Defect Detection Method Based on Domain Correlation
Jiyan Dai, Minghua Chen, Shuaijie Wu, et al.
Communications in computer and information science (2024), pp. 86-102
Closed Access
Quantitative Assessment of Pipeline Defects Utilizing a Dual-Stage Deep Learning Framework: Integration of Pretrained Yolov8 and Cnn Architectures on Magnetic Flux Leakage Data
Jialiang Xie, Jie Yang, Kuan Fu, et al.
(2024)
Closed Access
Research on Signal Quantization Method for Internal Detection of Composite Defects in Pipeline Welds Using Weak Magnetic Method
Bin Liu, Zheng Lian, Hui Yu, et al.
(2024)
Closed Access
MEM-RCNN: A Deep Learning Based Image Segmentation Algorithm for Pipeline Magnetic Leakage Defects
Zhujun Wang, Zhenyang Liu
(2023), pp. 202-205
Closed Access
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