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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:

Electroencephalography based fatigue detection using a novel feature fusion and extreme learning machine
Jichi Chen, Hong Wang, Chengcheng Hua
Cognitive Systems Research (2018) Vol. 52, pp. 715-728
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

A Review of EEG Signal Features and Their Application in Driver Drowsiness Detection Systems
Igor Stančin, Mario Cifrek, Alan Jović
Sensors (2021) Vol. 21, Iss. 11, pp. 3786-3786
Open Access | Times Cited: 182
The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review
Zouhair Elamrani Abou Elassad, Hajar Mousannif, Hassan Al Moatassime, et al.
Engineering Applications of Artificial Intelligence (2019) Vol. 87, pp. 103312-103312
Closed Access | Times Cited: 168
Identification and classification of construction equipment operators' mental fatigue using wearable eye-tracking technology
Jue Li, Heng Li, Waleed Umer, et al.
Automation in Construction (2019) Vol. 109, pp. 103000-103000
Open Access | Times Cited: 144
A Graph Theory-Based Modeling of Functional Brain Connectivity Based on EEG: A Systematic Review in the Context of Neuroergonomics
Lina Ismail, Waldemar Karwowski
IEEE Access (2020) Vol. 8, pp. 155103-155135
Open Access | Times Cited: 91
Data fusion for ITS: A systematic literature review
Chahinez Ounoughi, Sadok Ben Yahia
Information Fusion (2022) Vol. 89, pp. 267-291
Closed Access | Times Cited: 66
Driver fatigue detection based on improved YOLOv7
Xianguo Li, Xueyan Li, Zhenqian Shen, et al.
Journal of Real-Time Image Processing (2024) Vol. 21, Iss. 3
Closed Access | Times Cited: 8
Systematic Analysis of a Military Wearable Device Based on a Multi-Level Fusion Framework: Research Directions
Han Shi, Zhao Hai, Yang Liu, et al.
Sensors (2019) Vol. 19, Iss. 12, pp. 2651-2651
Open Access | Times Cited: 61
A recurrence network-based convolutional neural network for fatigue driving detection from EEG
Zhongke Gao, Yanli Li, Yuxuan Yang, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2019) Vol. 29, Iss. 11
Closed Access | Times Cited: 60
Characteristics of driver fatigue and fatigue-relieving effect of special light belt in extra-long highway tunnel: A real-road driving study
Pengcheng Qin, Mingnian Wang, Zhanwen Chen, et al.
Tunnelling and Underground Space Technology (2021) Vol. 114, pp. 103990-103990
Closed Access | Times Cited: 48
Validation and interpretation of a multimodal drowsiness detection system using explainable machine learning
Md. Mahmudul Hasan, Christopher N. Watling, Grégoire S. Larue
Computer Methods and Programs in Biomedicine (2023) Vol. 243, pp. 107925-107925
Open Access | Times Cited: 16
Study on tower crane drivers’ fatigue detection based on conditional empirical mode decomposition and multi-scale attention convolutional neural network
Daping Chen, Fuwang Wang
Biomedical Signal Processing and Control (2025) Vol. 105, pp. 107662-107662
Closed Access
Sensitivity and specificity of the driver sleepiness detection methods using physiological signals: A systematic review
Christopher N. Watling, Md. Mahmudul Hasan, Grégoire S. Larue
Accident Analysis & Prevention (2020) Vol. 150, pp. 105900-105900
Closed Access | Times Cited: 34
Research on Channel Selection and Multi-Feature Fusion of EEG Signals for Mental Fatigue Detection
Quan Liu, Yang Liu, Kun Chen, et al.
Entropy (2021) Vol. 23, Iss. 4, pp. 457-457
Open Access | Times Cited: 29
Automated detection of driver fatigue from electroencephalography through wavelet-based connectivity
Amirmasoud Ahmadi, Hanieh Bazregarzadeh, Kamran Kazemi
Journal of Applied Biomedicine (2020) Vol. 41, Iss. 1, pp. 316-332
Closed Access | Times Cited: 31
Rhythm-Dependent Multilayer Brain Network for the Detection of Driving Fatigue
Weidong Dang, Zhongke Gao, Dongmei Lv, et al.
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 25, Iss. 3, pp. 693-700
Closed Access | Times Cited: 29
Fatigue driving detection based on electrooculography: a review
Yuanyuan Tian, Jingyu Cao
EURASIP Journal on Image and Video Processing (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 24
Predicting time-varying, speed-varying dilemma zones using machine learning and continuous vehicle tracking
Moynur Rahman, Min-Wook Kang, Pranesh Biswas
Transportation Research Part C Emerging Technologies (2021) Vol. 130, pp. 103310-103310
Closed Access | Times Cited: 23
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional Connectivity
Naishi Feng, Fo Hu, Hong Wang, et al.
International Journal of Neural Systems (2021) Vol. 31, Iss. 12
Closed Access | Times Cited: 23
Two-dimensional phase lag index image representation of electroencephalography for automated recognition of driver fatigue using convolutional neural network
Jichi Chen, Shijie Wang, Enqiu He, et al.
Expert Systems with Applications (2021) Vol. 191, pp. 116339-116339
Closed Access | Times Cited: 22
Convolutional neural network with transfer learning approach for detection of unfavorable driving state using phase coherence image
Jichi Chen, Hong Wang, Shjie Wang, et al.
Expert Systems with Applications (2021) Vol. 187, pp. 116016-116016
Closed Access | Times Cited: 19
Environmental screening model of driving behavior for an electric bus entering and leaving stops
Yali Zhang, Rui Fu, Yingshi Guo, et al.
Transportation Research Part D Transport and Environment (2022) Vol. 112, pp. 103464-103464
Closed Access | Times Cited: 12
Sample-Entropy-Based Method for Real Driving Fatigue Detection with Multichannel Electroencephalogram
Tao Zhang, Jichi Chen, Enqiu He, et al.
Applied Sciences (2021) Vol. 11, Iss. 21, pp. 10279-10279
Open Access | Times Cited: 13
A Systematic Literature Review on Machine Learning Algorithms for Human Status Detection
Suman Kalyan Sardar, Naveen Kumar, Seul Chan Lee
IEEE Access (2022) Vol. 10, pp. 74366-74382
Open Access | Times Cited: 9
A fuzzy-based driver assistance system using human cognitive parameters and driving style information
Juan Pablo Vásconez, Michelle Viscaíno, Leonardo Guevara, et al.
Cognitive Systems Research (2020) Vol. 64, pp. 174-190
Open Access | Times Cited: 13
The functional brain network based on the combination of shortest path tree and its application in fatigue driving state recognition and analysis of the neural mechanism of fatigue driving
Shuli Zou, Taorong Qiu, Peifan Huang, et al.
Biomedical Signal Processing and Control (2020) Vol. 62, pp. 102129-102129
Closed Access | Times Cited: 12
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