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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:

Deep Review of Machine Learning Techniques on Detection of Drowsiness Using EEG Signal
Venkata Phanikrishna Balam, Allam Jaya Prakash, Suchismitha Chinara
IETE Journal of Research (2021) Vol. 69, Iss. 6, pp. 3104-3119
Closed Access | Times Cited: 17

Showing 17 citing articles:

A pilot study on AI-driven approaches for classification of mental health disorders
Naman Dhariwal, Nidhi Sengupta, M. Madiajagan, et al.
Frontiers in Human Neuroscience (2024) Vol. 18
Open Access | Times Cited: 8
A CNN-Based Wearable System for Driver Drowsiness Detection
Yongkai Li, Shuai Zhang, Gancheng Zhu, et al.
Sensors (2023) Vol. 23, Iss. 7, pp. 3475-3475
Open Access | Times Cited: 21
Real-time anti-sleep alert algorithm to prevent road accidents to ensure road safety
Abhishek Kumar Pathak, Ankit Kumar Singh, Pankaj Kumar, et al.
Frontiers in Future Transportation (2025) Vol. 6
Open Access
Applying Neural Networks with Time-Frequency Features for the Detection of Mental Fatigue
Ioannis Zorzos, Iοannis Kakkos, Stavros-Theofanis Miloulis, et al.
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1512-1512
Open Access | Times Cited: 11
TFAC-Net: A Temporal-Frequential Attentional Convolutional Network for Driver Drowsiness Recognition With Single-Channel EEG
Peiliang Gong, Pengpai Wang, Yueying Zhou, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 7, pp. 7004-7016
Closed Access | Times Cited: 4
Deep Learning-Based Attention Mechanism for Automatic Drowsiness Detection Using EEG Signal
Chiranjeevulu Divvala, Madhusudhan Mishra
IEEE Sensors Letters (2024) Vol. 8, Iss. 3, pp. 1-4
Closed Access | Times Cited: 2
Customized deep learning algorithm for drowsiness detection using single-channel EEG signal
Allam Jaya Prakash, Saunak Samantray, Chinmaya Behara, et al.
Elsevier eBooks (2022), pp. 189-201
Closed Access | Times Cited: 11
A survey on visual and non-visual features in Driver’s drowsiness detection
Nageshwar Nath Pandey, Naresh Babu Muppalaneni
Multimedia Tools and Applications (2022) Vol. 81, Iss. 26, pp. 38175-38215
Closed Access | Times Cited: 11
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
Design of high performance and energy efficient convolution array for convolution neural network-based image inference engine
S. Deepika, V. Arunachalam
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106953-106953
Closed Access | Times Cited: 2
Driver fatigue detection method based on multi-feature empirical fusion model
Yanbin Qin, Hongming Lyu, Kaibin Zhu
Multimedia Tools and Applications (2024)
Closed Access
Fusing convolutional learning and attention-based Bi-LSTM networks for early Alzheimer’s diagnosis from EEG signals towards IoMT
Mohammad R. Khosravi, Hossein Parsaei, Khosro Rezaee, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Classifying the physical activity indicator using machine learning and direct measurements: a feasibility study
Oswaldo Rivera, Oscar Fernando Avilés Sánchez, Eduardo Castillo-Castañeda
Acta Scientiarum. Technology/Acta scientiarum. Technology (2023) Vol. 45, pp. e61317-e61317
Open Access | Times Cited: 1
EEG based Mental Stress Detection using Deep Learning Techniques
Maryam Tahira, Prerna Vyas
(2023), pp. 1-7
Closed Access | Times Cited: 1
Analysis of EEG Signal for Drowsy Detection: A Machine Learning Approach
Venkata Phanikrishna Balam, Suchismita Chinara
Studies in computational intelligence (2021), pp. 147-164
Closed Access | Times Cited: 2
CogniDriveML: Detecting Drowsiness through Machine Learning with EEG Signals
Md Habibur Rahman, Omar Faroque, Mazharul Islam, et al.
(2023), pp. 1-5
Closed Access
Perception without preconception: comparison between the human and machine learner in recognition of tissues from histological sections
Sanghita Barui, Parikshit Sanyal, K. S. Rajmohan, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access
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