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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 Convolutional Neural Networks for mental load classification based on EEG data
Zhicheng Jiao, Xinbo Gao, Ying Wang, et al.
Pattern Recognition (2017) Vol. 76, pp. 582-595
Closed Access | Times Cited: 211

Showing 1-25 of 211 citing articles:

Deep learning for electroencephalogram (EEG) classification tasks: a review
Alexander Craik, Yongtian He, José L. Contreras-Vidal
Journal of Neural Engineering (2019) Vol. 16, Iss. 3, pp. 031001-031001
Open Access | Times Cited: 1218
Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals
Ji-Hoon Jeong, Kyung-Hwan Shim, Dong‐Joo Kim, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 5, pp. 1226-1238
Closed Access | Times Cited: 242
Learning Spatial–Spectral–Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment
Pengbo Zhang, Xue Wang, Weihang Zhang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2018) Vol. 27, Iss. 1, pp. 31-42
Closed Access | Times Cited: 195
Deep Learning in the Biomedical Applications: Recent and Future Status
Ryad Zemouri, Noureddine Zerhouni, Daniel Racoceanu
Applied Sciences (2019) Vol. 9, Iss. 8, pp. 1526-1526
Open Access | Times Cited: 161
RETRACTED ARTICLE: EEG signal classification using LSTM and improved neural network algorithms
P. Nagabushanam, S. Thomas George, S. Radha
Soft Computing (2019) Vol. 24, Iss. 13, pp. 9981-10003
Closed Access | Times Cited: 151
TSception: Capturing Temporal Dynamics and Spatial Asymmetry From EEG for Emotion Recognition
Yi Ding, Neethu Robinson, Su Zhang, et al.
IEEE Transactions on Affective Computing (2022) Vol. 14, Iss. 3, pp. 2238-2250
Open Access | Times Cited: 149
Motor Imagery Classification via Temporal Attention Cues of Graph Embedded EEG Signals
Dalin Zhang, Kaixuan Chen, Jian Debao, et al.
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 24, Iss. 9, pp. 2570-2579
Closed Access | Times Cited: 139
Neural Decoding of EEG Signals with Machine Learning: A Systematic Review
Maham Saeidi, Waldemar Karwowski, Farzad V. Farahani, et al.
Brain Sciences (2021) Vol. 11, Iss. 11, pp. 1525-1525
Open Access | Times Cited: 132
Brainwave-driven human-robot collaboration in construction
Yizhi Liu, Mahmoud Habibnezhad, Houtan Jebelli
Automation in Construction (2021) Vol. 124, pp. 103556-103556
Closed Access | Times Cited: 116
MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification
Phairot Autthasan, Rattanaphon Chaisaen, Thapanun Sudhawiyangkul, et al.
IEEE Transactions on Biomedical Engineering (2021) Vol. 69, Iss. 6, pp. 2105-2118
Open Access | Times Cited: 106
Cognitive Workload Recognition Using EEG Signals and Machine Learning: A Review
Yueying Zhou, Shuo Huang, Ziming Xu, et al.
IEEE Transactions on Cognitive and Developmental Systems (2021) Vol. 14, Iss. 3, pp. 799-818
Closed Access | Times Cited: 104
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-Resolved EEG Motor Imagery Signals
Yimin Hou, Shuyue Jia, Xiangmin Lun, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 6, pp. 7312-7323
Open Access | Times Cited: 97
LGGNet: Learning From Local-Global-Graph Representations for Brain–Computer Interface
Yi Ding, Neethu Robinson, Chengxuan Tong, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 7, pp. 9773-9786
Open Access | Times Cited: 51
Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification
Yongbo Liang, Zhencheng Chen, Rabab Ward, et al.
Biosensors (2018) Vol. 8, Iss. 4, pp. 101-101
Open Access | Times Cited: 148
A novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN
Yimin Hou, Lu Zhou, Shuyue Jia, et al.
Journal of Neural Engineering (2019) Vol. 17, Iss. 1, pp. 016048-016048
Open Access | Times Cited: 127
Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network
Tian-jian Luo, Changle Zhou, Fei Chao
BMC Bioinformatics (2018) Vol. 19, Iss. 1
Open Access | Times Cited: 126
The Use of Deep Learning to Predict Stroke Patient Mortality
Song-Hee Cheon, Jungyoon Kim, Jihye Lim
International Journal of Environmental Research and Public Health (2019) Vol. 16, Iss. 11, pp. 1876-1876
Open Access | Times Cited: 125
A LightGBM-Based EEG Analysis Method for Driver Mental States Classification
Hong Zeng, Yang Chen, Hua Zhang, et al.
Computational Intelligence and Neuroscience (2019) Vol. 2019, pp. 1-11
Open Access | Times Cited: 109
A Deep Learning Approach for Mild Depression Recognition Based on Functional Connectivity Using Electroencephalography
Xiaowei Li, Rong La, Ying Wang, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 98
Deep learning for EEG data analytics: A survey
Gen Li, Chang Ha Lee, Jason J. Jung, et al.
Concurrency and Computation Practice and Experience (2019) Vol. 32, Iss. 18
Closed Access | Times Cited: 90
A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction
Xiaodan Zhang, Xinbo Gao, Wen Lu, et al.
IEEE Transactions on Multimedia (2019) Vol. 21, Iss. 11, pp. 2815-2826
Closed Access | Times Cited: 88
Hybrid Deep Learning (hDL)-Based Brain-Computer Interface (BCI) Systems: A Systematic Review
Nibras Abo Alzahab, Luca Apollonio, Angelo Di Iorio, et al.
Brain Sciences (2021) Vol. 11, Iss. 1, pp. 75-75
Open Access | Times Cited: 83
TSception:A Deep Learning Framework for Emotion Detection Using EEG
Yi Ding, Neethu Robinson, Qiuhao Zeng, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2020), pp. 1-7
Open Access | Times Cited: 81
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period
Shu Gong, Kaibo Xing, Andrzej Cichocki, et al.
IEEE Transactions on Cognitive and Developmental Systems (2021) Vol. 14, Iss. 2, pp. 348-365
Open Access | Times Cited: 73
EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG With an Application to Emotion Recognition
Zhen Liang, Rushuang Zhou, Li Zhang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 1913-1925
Open Access | Times Cited: 59
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