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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:

EmotionMeter: A Multimodal Framework for Recognizing Human Emotions
Wei‐Long Zheng, Wei Liu, Yifei Lu, et al.
IEEE Transactions on Cybernetics (2018) Vol. 49, Iss. 3, pp. 1110-1122
Closed Access | Times Cited: 768

Showing 1-25 of 768 citing articles:

Deep learning-based electroencephalography analysis: a systematic review
Yannick Roy, Hubert Banville, Isabela Albuquerque, et al.
Journal of Neural Engineering (2019) Vol. 16, Iss. 5, pp. 051001-051001
Open Access | Times Cited: 1015
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
Peixiang Zhong, Di Wang, Chunyan Miao
IEEE Transactions on Affective Computing (2020) Vol. 13, Iss. 3, pp. 1290-1301
Open Access | Times Cited: 495
Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition
Dalin Zhang, Lina Yao, Kaixuan Chen, et al.
IEEE Transactions on Cybernetics (2019) Vol. 50, Iss. 7, pp. 3033-3044
Closed Access | Times Cited: 310
Transfer Learning for EEG-Based Brain–Computer Interfaces: A Review of Progress Made Since 2016
Dongrui Wu, Yifan Xu, Bao‐Liang Lu
IEEE Transactions on Cognitive and Developmental Systems (2020) Vol. 14, Iss. 1, pp. 4-19
Open Access | Times Cited: 252
Cross-Subject Emotion Recognition Using Flexible Analytic Wavelet Transform From EEG Signals
Vipin Gupta, Mayur Dahyabhai Chopda, Ram Bilas Pachori
IEEE Sensors Journal (2018) Vol. 19, Iss. 6, pp. 2266-2274
Closed Access | Times Cited: 249
EEG Based Emotion Recognition: A Tutorial and Review
Xiang Li, Yazhou Zhang, Prayag Tiwari, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 4, pp. 1-57
Open Access | Times Cited: 227
A Novel Bi-Hemispheric Discrepancy Model for EEG Emotion Recognition
Yang Li, Lei Wang, Wenming Zheng, et al.
IEEE Transactions on Cognitive and Developmental Systems (2020) Vol. 13, Iss. 2, pp. 354-367
Open Access | Times Cited: 223
EEG-Based BCI Emotion Recognition: A Survey
Edgar P. Torres, Edgar A. Torres, Myriam Hernández-Álvarez, et al.
Sensors (2020) Vol. 20, Iss. 18, pp. 5083-5083
Open Access | Times Cited: 219
Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition
Wei Liu, Jielin Qiu, Wei‐Long Zheng, et al.
IEEE Transactions on Cognitive and Developmental Systems (2022) Vol. 14, Iss. 2, pp. 715-729
Closed Access | Times Cited: 200
An Efficient LSTM Network for Emotion Recognition From Multichannel EEG Signals
Xiaobing Du, Cuixia Ma, Guanhua Zhang, et al.
IEEE Transactions on Affective Computing (2020) Vol. 13, Iss. 3, pp. 1528-1540
Open Access | Times Cited: 195
Deep Learning in Physiological Signal Data: A Survey
Beanbonyka Rim, Nak-Jun Sung, Se Dong Min, et al.
Sensors (2020) Vol. 20, Iss. 4, pp. 969-969
Open Access | Times Cited: 188
Emotion recognition based on EEG feature maps through deep learning network
Ante Topic, Mladen Russo
Engineering Science and Technology an International Journal (2021) Vol. 24, Iss. 6, pp. 1442-1454
Open Access | Times Cited: 174
Emotion recognition with convolutional neural network and EEG-based EFDMs
Fei Wang, Shichao Wu, Weiwei Zhang, et al.
Neuropsychologia (2020) Vol. 146, pp. 107506-107506
Open Access | Times Cited: 166
Multimodal data as a means to understand the learning experience
Michail N. Giannakos, Kshitij Sharma, Ilias O. Pappas, et al.
International Journal of Information Management (2019) Vol. 48, pp. 108-119
Open Access | Times Cited: 161
Emotion Recognition using Multimodal Residual LSTM Network
Jiaxin Ma, Hao Tang, Wei‐Long Zheng, et al.
Proceedings of the 30th ACM International Conference on Multimedia (2019), pp. 176-183
Closed Access | Times Cited: 160
Self-Supervised Learning for Electroencephalography
Mohammad Hossein Rafiei, Lynne V. Gauthier, Hojjat Adeli, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 2, pp. 1457-1471
Closed Access | Times Cited: 157
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4758-4758
Open Access | Times Cited: 156
Brain-Computer Interface: Advancement and Challenges
M. F. Mridha, Sujoy Chandra Das, Md. Mohsin Kabir, et al.
Sensors (2021) Vol. 21, Iss. 17, pp. 5746-5746
Open Access | Times Cited: 146
Investigating EEG-based functional connectivity patterns for multimodal emotion recognition
Xun Wu, Wei‐Long Zheng, Ziyi Li, et al.
Journal of Neural Engineering (2022) Vol. 19, Iss. 1, pp. 016012-016012
Open Access | Times Cited: 139
Emotion Recognition From Multimodal Physiological Signals Using a Regularized Deep Fusion of Kernel Machine
Xiaowei Zhang, Jinyong Liu, Jian Shen, et al.
IEEE Transactions on Cybernetics (2020) Vol. 51, Iss. 9, pp. 4386-4399
Closed Access | Times Cited: 136
Differences first in asymmetric brain: A bi-hemisphere discrepancy convolutional neural network for EEG emotion recognition
Dongmin Huang, Sentao Chen, Cheng Liu, et al.
Neurocomputing (2021) Vol. 448, pp. 140-151
Closed Access | Times Cited: 116
Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
Smith K. Khare, Victoria Blanes‐Vidal, Esmaeil S. Nadimi, et al.
Information Fusion (2023) Vol. 102, pp. 102019-102019
Open Access | Times Cited: 116
Review of challenges associated with the EEG artifact removal methods
Wajid Mumtaz, Suleman Rasheed, Alina Irfan
Biomedical Signal Processing and Control (2021) Vol. 68, pp. 102741-102741
Closed Access | Times Cited: 114
MS-MDA: Multisource Marginal Distribution Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognition
Hao Chen, Ming Jin, Zhunan Li, et al.
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 104
A study of deep learning approach for the classification of electroencephalogram (EEG) brain signals
Dharmendra Pathak, Ramgopal Kashyap, Surendra Rahamatkar
Elsevier eBooks (2022), pp. 133-144
Closed Access | Times Cited: 85
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