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 review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning
Fan Liu, Delong Chen, Jun Zhou, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105399-105399
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Fatigue at the wheel: A non-visual approach to truck driver fatigue detection by multi-feature fusion
Chen He, Pengpeng Xu, Xin Pei, et al.
Accident Analysis & Prevention (2024) Vol. 199, pp. 107511-107511
Closed Access | Times Cited: 12

TFormer: A time–frequency Transformer with batch normalization for driver fatigue recognition
Ruilin Li, Minghui Hu, Ruobin Gao, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102575-102575
Closed Access | Times Cited: 11

A review of driver gaze estimation and application in gaze behavior understanding
Pavan kumar Sharma, Pranamesh Chakraborty
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108117-108117
Open Access | Times Cited: 8

An enhanced ensemble deep random vector functional link network for driver fatigue recognition
Ruilin Li, Ruobin Gao, Liqiang Yuan, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106237-106237
Open Access | Times Cited: 18

EEG-based neural networks approaches for fatigue and drowsiness detection: A survey
Alice Othmani, Aznul Qalid Md Sabri, Sinem Aslan, et al.
Neurocomputing (2023) Vol. 557, pp. 126709-126709
Open Access | Times Cited: 18

A sophisticated Drowsiness Detection System via Deep Transfer Learning for real time scenarios
Amina Turki, Omar Kahouli, Saleh Albadran, et al.
AIMS Mathematics (2024) Vol. 9, Iss. 2, pp. 3211-3234
Open Access | Times Cited: 6

Visual-Based Obstacle Avoidance Method Using Advanced CNN for Mobile Robots
Oğuz Mısır, Muhammed ÇELİK
Internet of Things (2025), pp. 101538-101538
Closed Access

A multidimensional adaptive transformer network for fatigue detection
Dingming Wu, Liu Deng, Qiang Lü, et al.
Cognitive Neurodynamics (2025) Vol. 19, Iss. 1
Closed Access

Attention-Guided Multiscale Convolutional Neural Network for Driving Fatigue Detection
Jinbu Tang, Wei Zhou, Wei‐Long Zheng, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 14, pp. 23280-23290
Closed Access | Times Cited: 3

Driver vigilance detection based on deep learning with fused thermal image information for public transportation
Zijie Zhou, Zheng Fang, Jirui Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106604-106604
Closed Access | Times Cited: 9

A multi-modal driver emotion dataset and study: Including facial expressions and synchronized physiological signals
Guoliang Xiang, Song Yao, Hanwen Deng, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 130, pp. 107772-107772
Closed Access | Times Cited: 9

Facial feature fusion convolutional neural network for driver fatigue detection
Zhichao Sun, Yinan Miao, Jun Young Jeon, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106981-106981
Closed Access | Times Cited: 8

Driver distraction detection using semi-supervised lightweight vision transformer
Adam A. Q. Mohammed, Xin Geng, Jing Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107618-107618
Closed Access | Times Cited: 8

A New Method for Detecting the Fatigue Using Automated Deep Learning Techniques for Medical Imaging Applications
Naveen Sundar Gnanadesigan, G. A. Lincoln, Narmadha Dhanasegar, et al.
Wireless Personal Communications (2024) Vol. 135, Iss. 2, pp. 1009-1034
Closed Access | Times Cited: 1

A Multi-Source Fusion Approach for Driver Fatigue Detection Using Physiological Signals and Facial Image
Yong Peng, Hanwen Deng, Guoliang Xiang, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 11, pp. 16614-16624
Closed Access | Times Cited: 1

Fatigue detection method for UAV remote pilot based on multi feature fusion
Lei Pan, Chongyao Yan, Zheng Yuan, et al.
Electronic Research Archive (2022) Vol. 31, Iss. 1, pp. 442-466
Open Access | Times Cited: 4

Driver identification and fatigue detection algorithm based on deep learning
Yuhua Ma, Tao Ye, Yuandan Gong, et al.
Mathematical Biosciences & Engineering (2023) Vol. 20, Iss. 5, pp. 8162-8189
Open Access | Times Cited: 2

Driver alertness monitoring system in the context of safety increasing and sustainable energy use
Florin Bogdan Scurt, Horia Beleș, Tiberiu Vesselényi, et al.
Cognitive Sustainability (2023) Vol. 2, Iss. 1
Open Access | Times Cited: 2

Improved SSD for crew fatigue driving detection algorithm
Pichuang Liu, Hao Zhang, Yingjie Xiao, et al.
(2024), pp. 28-28
Closed Access

Research on Deep Learning-based Driver Fatigue Driving Behavior Recognition Methods
Miao Sun, Fan Liu, Haijun He, et al.
(2024), pp. 106-109
Closed Access

Driver fatigue detection method based on multi-feature empirical fusion model
Yanbin Qin, Hongming Lyu, Kaibin Zhu
Multimedia Tools and Applications (2024)
Closed Access

CLASSIFICATION OF X-RAY AND CT IMAGES IN DIFFERENT COLOR SPACES USING ROBUST CNN
Nesrin Aydın Atasoy, İrem Kura
Mühendislik Bilimleri ve Tasarım Dergisi (2024) Vol. 12, Iss. 3, pp. 505-516
Open Access

Leveraging Context-Aware Emotion and Fatigue Recognition Through Large Language Models for Enhanced Advanced Driver Assistance Systems (ADAS)
Vahid Tavakkoli, Kabeh Mohsenzadegan, Kyandoghere Kyamakya
Studies in computational intelligence (2024), pp. 49-85
Closed Access

The nexus of intelligent transportation: A lightweight Bi-input fusion detection model for autonomous-rail rapid transit
Hongjie Tang, Jirui Wang, Jiaoyi Wu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109705-109705
Closed Access

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