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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:

Brain wave classification using long short-term memory network based OPTICAL predictor
Shiu Kumar, Alok Sharma, Tatsuhiko Tsunoda
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 107

Showing 1-25 of 107 citing articles:

Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: a review
Hamdi Altaheri, Ghulam Muhammad, Mansour Alsulaiman, et al.
Neural Computing and Applications (2021) Vol. 35, Iss. 20, pp. 14681-14722
Closed Access | Times Cited: 321
BrainMRNet: Brain tumor detection using magnetic resonance images with a novel convolutional neural network model
Mesut Toğaçar, Burhan Ergen, Zafer Cömert
Medical Hypotheses (2019) Vol. 134, pp. 109531-109531
Closed Access | Times Cited: 241
Improving Effectiveness of Different Deep Transfer Learning-Based Models for Detecting Brain Tumors From MR Images
Sohaib Asif, Wenhui Yi, Qurrat Ul Ain, et al.
IEEE Access (2022) Vol. 10, pp. 34716-34730
Open Access | Times Cited: 129
Exploiting pretrained CNN models for the development of an EEG-based robust BCI framework
Muhammad Tariq Sadiq, Muhammad Zulkifal Aziz, Ahmad Almogren, et al.
Computers in Biology and Medicine (2022) Vol. 143, pp. 105242-105242
Closed Access | Times Cited: 73
An EEG channel selection method for motor imagery based brain–computer interface and neurofeedback using Granger causality
Hesam Varsehi, Mohammad Firoozabadi
Neural Networks (2020) Vol. 133, pp. 193-206
Closed Access | Times Cited: 102
Automated Detection of Sleep Stages Using Deep Learning Techniques: A Systematic Review of the Last Decade (2010–2020)
Hui Wen Loh, Chui Ping Ooi, Jahmunah Vicnesh, et al.
Applied Sciences (2020) Vol. 10, Iss. 24, pp. 8963-8963
Open Access | Times Cited: 91
Evaluating the Potential and Challenges of an Uncertainty Quantification Method for Long Short‐Term Memory Models for Soil Moisture Predictions
Kuai Fang, Daniel Kifer, Kathryn Lawson, et al.
Water Resources Research (2020) Vol. 56, Iss. 12
Open Access | Times Cited: 87
Toward the Development of Versatile Brain–Computer Interfaces
Muhammad Tariq Sadiq, Xiaojun Yu, Zhaohui Yuan, et al.
IEEE Transactions on Artificial Intelligence (2021) Vol. 2, Iss. 4, pp. 314-328
Open Access | Times Cited: 76
2D MRI image analysis and brain tumor detection using deep learning CNN model LeU-Net
Hari Mohan, Kalyan Chatterjee
Multimedia Tools and Applications (2021) Vol. 80, Iss. 28-29, pp. 36111-36141
Closed Access | Times Cited: 64
A review of critical challenges in MI-BCI: From conventional to deep learning methods
Zahra Khademi, Farideh Ebrahimi, Hussain Montazery Kordy
Journal of Neuroscience Methods (2022) Vol. 383, pp. 109736-109736
Closed Access | Times Cited: 61
Classification of Motor Imagery EEG Signals Based on Deep Autoencoder and Convolutional Neural Network Approach
Jamal F. Hwaidi, Tom Chen
IEEE Access (2022) Vol. 10, pp. 48071-48081
Open Access | Times Cited: 39
Computer-Aided Early Melanoma Brain-Tumor Detection Using Deep-Learning Approach
Rimsha Asad, Saif Ur Rehman, Azhar Imran, et al.
Biomedicines (2023) Vol. 11, Iss. 1, pp. 184-184
Open Access | Times Cited: 26
Brain tumor detection based on hybrid deep neural network in MRI by adaptive squirrel search optimization
Daizy Deb, Sudipta Roy
Multimedia Tools and Applications (2020) Vol. 80, Iss. 2, pp. 2621-2645
Closed Access | Times Cited: 62
Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off
Javier León, Juan José Escobar, Andrés Ortíz, et al.
PLoS ONE (2020) Vol. 15, Iss. 6, pp. e0234178-e0234178
Open Access | Times Cited: 53
Stress Classification Using Brain Signals Based on LSTM Network
Nishtha Phutela, Devanjali Relan, Goldie Gabrani, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-13
Open Access | Times Cited: 34
Improving NeuCube spiking neural network for EEG-based pattern recognition using transfer learning
Xuanyu Wu, Yixiong Feng, Shanhe Lou, et al.
Neurocomputing (2023) Vol. 529, pp. 222-235
Closed Access | Times Cited: 18
Rehabilitation with brain-computer interface and upper limb motor function in ischemic stroke: A randomized controlled trial
Anxin Wang, Xue Tian, Di Jiang, et al.
Med (2024) Vol. 5, Iss. 6, pp. 559-569.e4
Closed Access | Times Cited: 7
CTNet: a convolutional transformer network for EEG-based motor imagery classification
Wei Zhao, Xiaolu Jiang, Baocan Zhang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
DWT and CNN based multi-class motor imagery electroencephalographic signal recognition
Xunguang Ma, Dashuai Wang, Danhua Liu, et al.
Journal of Neural Engineering (2020) Vol. 17, Iss. 1, pp. 016073-016073
Closed Access | Times Cited: 40
The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Mamunur Rashid, Bifta Sama Bari, Md Jahid Hasan, et al.
PeerJ Computer Science (2021) Vol. 7, pp. e374-e374
Open Access | Times Cited: 39
OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals
Shiu Kumar, Ronesh Sharma, Alok Sharma
PeerJ Computer Science (2021) Vol. 7, pp. e375-e375
Open Access | Times Cited: 35
Recent Trends in EEG-Based Motor Imagery Signal Analysis and Recognition: A Comprehensive Review
Neha Sharma, Manoj Sharma, Amit Singhal, et al.
IEEE Access (2023) Vol. 11, pp. 80518-80542
Open Access | Times Cited: 14
Predicting Architectural Space Preferences Using EEG-Based Emotion Analysis: A CNN-LSTM Approach
Ju Eun Cho, Se Yeon Kang, Y. Hong, et al.
Applied Sciences (2025) Vol. 15, Iss. 8, pp. 4217-4217
Open Access
Deep learning in motor imagery EEG signal decoding: A Systematic Review
Aurora Saibene, Hafez Ghaemi, Eda Dağdevır
Neurocomputing (2024) Vol. 610, pp. 128577-128577
Closed Access | Times Cited: 4
Diagonal loading common spatial patterns with Pearson correlation coefficient based feature selection for efficient motor imagery classification
Hanaa S. Ali, Asmaa I. Ismail, El‐Sayed M. El‐Rabaie, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-15
Closed Access
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