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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:

Pipeline Magnetic Flux Leakage Image Detection Algorithm Based on Multiscale SSD Network
Lijian Yang, Zhujun Wang, Gao Song-wei
IEEE Transactions on Industrial Informatics (2019) Vol. 16, Iss. 1, pp. 501-509
Closed Access | Times Cited: 101

Showing 1-25 of 101 citing articles:

Pipeline In-Line Inspection Method, Instrumentation and Data Management
Qiuping Ma, Gui Yun Tian, Yanli Zeng, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3862-3862
Open Access | Times Cited: 123
Review on automated condition assessment of pipelines with machine learning
Yiming Liu, Yi Bao
Advanced Engineering Informatics (2022) Vol. 53, pp. 101687-101687
Closed Access | Times Cited: 103
MSC-DNet: An efficient detector with multi-scale context for defect detection on strip steel surface
Rongqiang Liu, Min Huang, Zheming Gao, et al.
Measurement (2023) Vol. 209, pp. 112467-112467
Closed Access | Times Cited: 83
Deep learning-based welding image recognition: A comprehensive review
Tianyuan Liu, Pai Zheng, Jinsong Bao
Journal of Manufacturing Systems (2023) Vol. 68, pp. 601-625
Closed Access | Times Cited: 39
Efficient Fused-Attention Model for Steel Surface Defect Detection
Ching-Chi Yeung, Kin‐Man Lam
IEEE Transactions on Instrumentation and Measurement (2022), pp. 1-1
Closed Access | Times Cited: 60
Yolo-MSAPF: Multiscale Alignment Fusion With Parallel Feature Filtering Model for High Accuracy Weld Defect Detection
Guan-Qiang Wang, Chizhou Zhang, Ming-Song Chen, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 26
Deep Learning for Magnetic Flux Leakage Detection and Evaluation of Oil & Gas Pipelines: A Review
Songling Huang, Lisha Peng, Hongyu Sun, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1372-1372
Open Access | Times Cited: 23
A cascaded deep learning approach for detecting pipeline defects via pretrained YOLOv5 and ViT models based on MFL data
Pengchao Chen, Rui Li, Kuan Fu, et al.
Mechanical Systems and Signal Processing (2023) Vol. 206, pp. 110919-110919
Closed Access | Times Cited: 22
Reliability analysis of corroded pipes using MFL signals and Residual Neural Networks
Yinuo Chen, Zhigang Tian, Haotian Wei, et al.
Process Safety and Environmental Protection (2024) Vol. 184, pp. 1131-1142
Closed Access | Times Cited: 9
A novel magnetic force transmission eddy current array probe and its application for nondestructive testing of defects in pipeline structures
Shejuan Xie, Zhirong Duan, Ji Li, et al.
Sensors and Actuators A Physical (2020) Vol. 309, pp. 112030-112030
Closed Access | Times Cited: 57
Improved MobileNetV2-SSDLite for automatic fabric defect detection system based on cloud-edge computing
Jiaqi Zhang, Junfeng Jing, Pengwen Lu, et al.
Measurement (2022) Vol. 201, pp. 111665-111665
Closed Access | Times Cited: 36
An Infrared Image Detection Method of Substation Equipment Combining Iresgroup Structure and CenterNet
Hanbo Zheng, Yaohui Cui, Wenqiang Yang, et al.
IEEE Transactions on Power Delivery (2022) Vol. 37, Iss. 6, pp. 4757-4765
Closed Access | Times Cited: 30
SSCT-Net: A Semisupervised Circular Teacher Network for Defect Detection With Limited Labeled Multiview MFL Samples
Xiangkai Shen, Jinhai Liu, Jiayue Sun, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 19, Iss. 10, pp. 10114-10124
Closed Access | Times Cited: 18
A Novel Cascaded Deep Learning Model for the Detection and Quantification of Defects in Pipelines via Magnetic Flux Leakage Signals
Veysel Yuksel, Yusuf Engin Tetik, Mahmut Omer Basturk, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-9
Closed Access | Times Cited: 18
Multi-classification recognition and quantitative characterization of surface defects in belt grinding based on YOLOv7
Zhu Bao, Guijian Xiao, Youdong Zhang, et al.
Measurement (2023) Vol. 216, pp. 112937-112937
Closed Access | Times Cited: 17
A Dynamic Weights-Based Wavelet Attention Neural Network for Defect Detection
Jinhai Liu, He Zhao, Zhaolin Chen, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 11, pp. 16211-16221
Closed Access | Times Cited: 16
A Rapid Screening Method for Suspected Defects in Steel Pipe Welds by Combining Correspondence Mechanism and Normalizing Flow
Wenqi Cui, Kechen Song, Yanyan Wang, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 9, pp. 11171-11180
Closed Access | Times Cited: 7
An Intelligent Defect Detection Approach Based on Cascade Attention Network Under Complex Magnetic Flux Leakage Signals
Jinhai Liu, Xiangkai Shen, Jianfeng Wang, et al.
IEEE Transactions on Industrial Electronics (2022) Vol. 70, Iss. 7, pp. 7417-7427
Closed Access | Times Cited: 27
Data Modeling Techniques for Pipeline Integrity Assessment: A State-of-the-Art Survey
Jiatong Ling, Ke Feng, Teng Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-17
Closed Access | Times Cited: 15
Research progress on coping strategies for the fluid-solid erosion wear of pipelines
Haiyue Yu, Haonan Liu, Shuaijun Zhang, et al.
Powder Technology (2023) Vol. 422, pp. 118457-118457
Closed Access | Times Cited: 14
Intelligent identification of girth welds defects in pipelines using neural networks with attention modules
Lushuai Xu, Shaohua Dong, Haotian Wei, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107295-107295
Closed Access | Times Cited: 13
Simulation Study of the Magnetic Gradient Method for Signal Detection Outside Buried Bimetallic Pipes
Chun Qing, X Zhang, Hong Pan, et al.
Lecture notes in mechanical engineering (2025), pp. 1061-1072
Open Access
Reconstruction of 3-D pipeline defect profile based on MFL signals and hybrid neural networks
Yinuo Chen, Zhigang Tian, Haotian Wei, et al.
Reliability Engineering & System Safety (2025), pp. 110890-110890
Open Access
Automatic Identification of Multi-Type Weld Seam Based on Vision Sensor With Silhouette-Mapping
Yingzhong Tian, Hongfei Liu, Long Li, et al.
IEEE Sensors Journal (2020) Vol. 21, Iss. 4, pp. 5402-5412
Closed Access | Times Cited: 32
Novel intelligent diagnosis method of oil and gas pipeline defects with transfer deep learning and feature fusion
Junming Yao, Wei Liang, Jingyi Xiong
International Journal of Pressure Vessels and Piping (2022) Vol. 200, pp. 104781-104781
Closed Access | Times Cited: 20
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