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:

Intrusion detection for high-speed railways based on unsupervised anomaly detection models
Yao Wang, Zujun Yu, Liqiang Zhu
Applied Intelligence (2022) Vol. 53, Iss. 7, pp. 8453-8466
Closed Access | Times Cited: 15

Showing 15 citing articles:

Intrusion detection in cloud computing based on time series anomalies utilizing machine learning
Abdel-Rahman Al-Ghuwairi, Yousef Sharrab, Dimah Al-Fraihat, et al.
Journal of Cloud Computing Advances Systems and Applications (2023) Vol. 12, Iss. 1
Open Access | Times Cited: 37

Railway Intrusion Detection Based on Machine Vision: A Survey, Challenges, and Perspectives
Zhiwei Cao, Yong Qin, Limin Jia, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 7, pp. 6427-6448
Closed Access | Times Cited: 8

SDRC-YOLO: A Novel Foreign Object Intrusion Detection Algorithm in Railway Scenarios
Caixia Meng, Zhaonan Wang, Lei Shi, et al.
Electronics (2023) Vol. 12, Iss. 5, pp. 1256-1256
Open Access | Times Cited: 18

Rail-PatchCore: unsupervised learning-based detection of visual anomalies in the railway-turnout environment
YuanHao Zhang, Zujun Yu, Liqiang Zhu, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access

RailFDNet: A hybrid supervision and feature discrepancy enhancement model for railway anomalous object detection
Tao Sun, Baoqing Guo, Tao Ruan, et al.
Expert Systems with Applications (2025) Vol. 275, pp. 127005-127005
Closed Access

FRAnomaly: flow-based rapid anomaly detection from images
Fran Milković, Luka Posilović, Duje Medak, et al.
Applied Intelligence (2024) Vol. 54, Iss. 4, pp. 3502-3515
Closed Access | Times Cited: 2

An Anomaly Detection Method for Railway Track Using Semi-supervised Learning and Vision-Lidar Decision Fusion
Xuanyu Ge, Zhiwei Cao, Yong Qin, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access | Times Cited: 1

Survey on video anomaly detection in dynamic scenes with moving cameras
Runyu Jiao, Yi Wan, Fabio Poiesi, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. S3, pp. 3515-3570
Closed Access | Times Cited: 3

Railway Intrusion Events Classification and Location Based on Deep Learning in Distributed Vibration Sensing
Jian Yang, Chen Wang, Jichao Yi, et al.
Symmetry (2022) Vol. 14, Iss. 12, pp. 2552-2552
Open Access | Times Cited: 5

Local and Global Information in Obstacle Detection on Railway Tracks
Matthias Brucker, Andrei Cramariuc, Cornelius von Einem, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2023), pp. 9049-9056
Open Access | Times Cited: 2

Multimodal anomaly detection for high-speed train control system based on attention mechanism
Renwei Kang, Yanzhi Pang, Jianfeng Cheng, et al.
Research Square (Research Square) (2024)
Open Access

Full-Dimensional Proportional-Derivative Control Technique for Turing Pattern and Bifurcation of Delayed Reaction-Diffusion Bidirectional Ring Neural Networks
Xiangyu Du, Min Xiao, Yifeng Luan, et al.
Journal of Computational and Nonlinear Dynamics (2024) Vol. 19, Iss. 9
Closed Access

A novel fusion feature imageization with improved extreme learning machine for network anomaly detection
Geying Yang, Jinyu Wu, Lina Wang, et al.
Applied Intelligence (2024) Vol. 54, Iss. 19, pp. 9313-9329
Closed Access

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