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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 Hybrid Driver Fatigue and Distraction Detection Model Using AlexNet Based on Facial Features
Salma Anber, Wafaa Alsaggaf, Wafaa M. Shalash
Electronics (2022) Vol. 11, Iss. 2, pp. 285-285
Open Access | Times Cited: 24

Showing 24 citing articles:

IoT-Assisted Automatic Driver Drowsiness Detection through Facial Movement Analysis Using Deep Learning and a U-Net-Based Architecture
Shiplu Das, Sanjoy Pratihar, Buddhadeb Pradhan, et al.
Information (2024) Vol. 15, Iss. 1, pp. 30-30
Open Access | Times Cited: 13
MobileNet-Based Architecture for Distracted Human Driver Detection of Autonomous Cars
Mahmoud Abdelkader Bashery Abbass, Yuseok Ban
Electronics (2024) Vol. 13, Iss. 2, pp. 365-365
Open Access | Times Cited: 6
A Novel Fatigue Detection Method Based on Video Transformer
Y Zhong, Shipeng Li, Yonghong Yang, et al.
Lecture notes in electrical engineering (2025), pp. 495-505
Closed Access
DDD TinyML: A TinyML-Based Driver Drowsiness Detection Model Using Deep Learning
Norah N. Alajlan, Dina M. Ibrahim
Sensors (2023) Vol. 23, Iss. 12, pp. 5696-5696
Open Access | Times Cited: 13
Feasibility Study on Contactless Feature Analysis for Early Drowsiness Detection in Driving Scenarios
Yebin Choi, Sihyeon Yang, Y Park, et al.
Electronics (2025) Vol. 14, Iss. 4, pp. 662-662
Open Access
Optimal feature tuning model by variants of convolutional neural network with LSTM for driver distract detection in IoT platform
Hameed Mutlag Farhan, Ayça Kurnaz Türkben, Raghda Awad Shaban Naseri
Knowledge and Information Systems (2025)
Open Access
Driver Fatigue and Distracted Driving Detection Using Random Forest and Convolutional Neural Network
Bing-Ting Dong, Huei‐Yung Lin, Chin‐Chen Chang
Applied Sciences (2022) Vol. 12, Iss. 17, pp. 8674-8674
Open Access | Times Cited: 15
A Real-Time Embedded System for Driver Drowsiness Detection Based on Visual Analysis of the Eyes and Mouth Using Convolutional Neural Network and Mouth Aspect Ratio
Ruben Florez, Facundo Palomino-Quispe, Ana Beatriz Alvarez, et al.
Sensors (2024) Vol. 24, Iss. 19, pp. 6261-6261
Open Access | Times Cited: 2
Efficient Eye State Detection for Driver Fatigue Monitoring Using Optimized YOLOv7-Tiny
Gwo-Ching Chang, Bohan Zeng, Shih-Chiang Lin
(2024)
Open Access | Times Cited: 1
Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey
Maha Yasir Jumhaa, Osama Majeed, Alaa Taima
BIO Web of Conferences (2024) Vol. 97, pp. 00007-00007
Open Access | Times Cited: 1
Illumination Intelligent Adaptation and Analysis Framework: A comprehensive solution for enhancing nighttime driving fatigue monitoring
Zenghui Tian, Nur Safinas Albakry, Yinghui Du
PLoS ONE (2024) Vol. 19, Iss. 8, pp. e0308201-e0308201
Open Access | Times Cited: 1
Data fusion for driver drowsiness recognition: A multimodal perspective
S. Priyanka, S. Shanthi, Ashok Kumar, et al.
Egyptian Informatics Journal (2024) Vol. 27, pp. 100529-100529
Open Access | Times Cited: 1
A State-of-the-Art Review of Deep Learning-Based Object Detection Methods and Techniques
Chhaya Gupta, Nasib Singh Gill, Preeti Gulia
Lecture notes in networks and systems (2024), pp. 477-492
Closed Access | Times Cited: 1
A survey of fatigue measures and models
Antonio Laverghetta, Minh‐Phuong Tran, Alec Braynen, et al.
The Journal of Defense Modeling and Simulation Applications Methodology Technology (2023), pp. 154851292311585-154851292311585
Closed Access | Times Cited: 3
Artificial intelligence modelling human mental fatigue: A comprehensive survey
Alexandre Lambert, Aakash Soni, Assia Soukane, et al.
Neurocomputing (2023) Vol. 567, pp. 126999-126999
Open Access | Times Cited: 2
SOMN_IA: Portable and Universal Device for Real-Time Detection of Driver’s Drowsiness and Distraction Levels
Jonathan Flores-Monroy, Mariko Nakano-Miyatake, Enrique Escamilla-Hernández, et al.
Electronics (2022) Vol. 11, Iss. 16, pp. 2558-2558
Open Access | Times Cited: 3
A review of techniques and methods for deep learning techniques in driver fatigue detection
Yawen Luo
Applied and Computational Engineering (2024) Vol. 31, Iss. 1, pp. 36-42
Open Access
Scaling effectivity in manifold methodologies to detect driver’s fatigueness and drowsiness state
Gowrishankar Shiva Shankara Chari, Jyothi Arcot Prashant
IAES International Journal of Artificial Intelligence (2024) Vol. 13, Iss. 2, pp. 1227-1227
Open Access
Efficient Eye State Detection for Driver Fatigue Monitoring Using Optimized YOLOv7-Tiny
Gwo-Ching Chang, Bohan Zeng, Shih-Chiang Lin
Applied Sciences (2024) Vol. 14, Iss. 8, pp. 3497-3497
Open Access
Comparison of Artificial Intelligent Systems for Real-Time Accident-Prone Applications
Venkata Subba Rao Are, T. Anuradha, Pooja Nagabhairu, et al.
Springer proceedings in mathematics & statistics (2024), pp. 683-690
Closed Access
Using machine learning to understand driving behavior patterns
Jorge Valente, Cláudia Ramalho, Pedro Vinha, et al.
Procedia Computer Science (2024) Vol. 239, pp. 1823-1830
Open Access
A Visualization-Based Ramp Event Detection Model for Wind Power Generation
Junwei Fu, Yuna Ni, Yuming Ma, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1166-1166
Open Access | Times Cited: 1
A Remote Fatigue Driving Detection System for Ship Supervision based on Physiological Response Features
Jinming Tong, Wei Cheng, Chen Li, et al.
(2023), pp. 191-196
Closed Access
Electric Bus Pedal Misapplication Detection Based on Phase Space Reconstruction Method
Aihong Lyu, Kunchen Li, Yali Zhang, et al.
Sensors (2023) Vol. 23, Iss. 18, pp. 7883-7883
Open Access
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