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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:

Emotion recognition using spatial-temporal EEG features through convolutional graph attention network
Zhongjie Li, Gaoyan Zhang, Longbiao Wang, et al.
Journal of Neural Engineering (2023) Vol. 20, Iss. 1, pp. 016046-016046
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Emotion recognition in EEG signals using deep learning methods: A review
Mahboobeh Jafari, Afshin Shoeibi, Marjane Khodatars, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107450-107450
Open Access | Times Cited: 74
MBCFNet: A Multimodal Brain–Computer Fusion Network for human intention recognition
Zhongjie Li, Gaoyan Zhang, Shogo Okada, et al.
Knowledge-Based Systems (2024) Vol. 296, pp. 111826-111826
Closed Access | Times Cited: 5
Dynamic domain adaptive EEG emotion recognition based on multi-source selection
Zhongmin Wang, Menghao Zhao
Review of Scientific Instruments (2025) Vol. 96, Iss. 1
Closed Access
Toward the Construction of Affective Brain-Computer Interface: A Systematic Review
Huayu Chen, Junxiang Li, Huanhuan He, et al.
ACM Computing Surveys (2025)
Closed Access
Graph convolution network-based eeg signal analysis: a review
Hui Xiong, Yan Yan, Yimei Chen, et al.
Medical & Biological Engineering & Computing (2025)
Closed Access
A Comparative Study on Prominent Connectivity Features for Emotion Recognition From EEG
Mahfuza Akter Maria, M. A. H. Akhand, A. B. M. Aowlad Hossain, et al.
IEEE Access (2023) Vol. 11, pp. 37809-37831
Open Access | Times Cited: 11
Unsupervised heterogeneous domain adaptation for EEG classification
Hanrui Wu, Qinmei Xie, Zhuliang Yu, et al.
Journal of Neural Engineering (2024) Vol. 21, Iss. 4, pp. 046018-046018
Closed Access | Times Cited: 3
Multimodal machine learning approach for emotion recognition using physiological signals
Mohamad A. Ramadan, Nancy M. Salem, Lamees N. Mahmoud, et al.
Biomedical Signal Processing and Control (2024) Vol. 96, pp. 106553-106553
Closed Access | Times Cited: 2
EEG Emotion Recognition Employing RGPCN-BiGRUAM: ReliefF-Based Graph Pooling Convolutional Network and BiGRU Attention Mechanism
Chao Jiang, Xinyi Sun, Yingying Dai, et al.
Electronics (2024) Vol. 13, Iss. 13, pp. 2530-2530
Open Access | Times Cited: 2
Emotion recognition based on EEG source signals and dynamic brain function network
He Sun, Hailing Wang, Raofen Wang, et al.
Journal of Neuroscience Methods (2024), pp. 110358-110358
Closed Access | Times Cited: 1
CEDNet: A Continuous Emotion Detection Network for Naturalistic Stimuli Using MEG Signals
Zeming He, Gaoyan Zhang
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2024), pp. 2001-2005
Closed Access | Times Cited: 1
TSANN-TG: Temporal–Spatial Attention Neural Networks with Task-Specific Graph for EEG Emotion Recognition
Chao Jiang, Yingying Dai, Yunheng Ding, et al.
Brain Sciences (2024) Vol. 14, Iss. 5, pp. 516-516
Open Access | Times Cited: 1
Multi-Domain Based Dynamic Graph Representation Learning for EEG Emotion Recognition
Hao Tang, Songyun Xie, Xinzhou Xie, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 9, pp. 5227-5238
Closed Access | Times Cited: 1
MSS-JDA: Multi-Source Self-Selected Joint Domain Adaptation method based on cross-subject EEG emotion recognition
Shinan Chen, Weifeng Ma, Yuchen Wang, et al.
Biomedical Signal Processing and Control (2024) Vol. 100, pp. 106953-106953
Closed Access | Times Cited: 1
LSTM-enhanced multi-view dynamical emotion graph representation for EEG signal recognition
Guixun Xu, Wenhui Guo, Yanjiang Wang
Journal of Neural Engineering (2023) Vol. 20, Iss. 3, pp. 036038-036038
Closed Access | Times Cited: 3
Generating personalized facial emotions using emotional EEG signals and conditional generative adversarial networks
Masoumeh Esmaeili, Kourosh Kiani
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 36013-36038
Closed Access | Times Cited: 2
High Variability Periods in the EEG Distinguish Cognitive Brain States
Dhanya Parameshwaran, Tara C. Thiagarajan
Brain Sciences (2023) Vol. 13, Iss. 11, pp. 1528-1528
Open Access | Times Cited: 2
EEG Emotion Recognition Based on Self-Distillation Convolutional Graph Attention Network
Chao Hao, Shuqi Feng
ICST Transactions on e-Education and e-Learning (2024) Vol. 10
Open Access
Enhancing EEG-Based Emotion Recognition Using Asymmetric Windowing Recurrence Plots
Dwi Wahyu Prabowo, Noor Akhmad Setiawan, Johan Debayle, et al.
IEEE Access (2024) Vol. 12, pp. 85969-85982
Open Access
GANN: EEG-based Emotion Classification Using Context-Aware Gated Attention Neural Network
Rand Alibrahim, Heba Kurdi
Procedia Computer Science (2024) Vol. 241, pp. 234-241
Open Access
INVESTIGATING NOVEL METHODS AND METRICS IN CONSUMER NEUROSCIENCE
Farzad Saffari
(2024)
Open Access
EEG emotion recognition approach using multi-scale convolution and feature fusion
Yong Zhang, Qingguo Shan, Wen‐Yun Chen, et al.
The Visual Computer (2024)
Closed Access
HASTF: a hybrid attention spatio-temporal feature fusion network for EEG emotion recognition
Fangzhou Hu, Fei Wang, Jinying Bi, et al.
Frontiers in Neuroscience (2024) Vol. 18
Open Access
ST-SHAP: A hierarchical and explainable attention network for emotional EEG representation learning and decoding
Minmin Miao, Liang Jin, Zhenzhen Sheng, et al.
Journal of Neuroscience Methods (2024) Vol. 414, pp. 110317-110317
Closed Access
Emotion Recognition from Brain Connectivity Based on Multi-Head Attention Transformer and Autoencoder Network
Farzad Saffari, Mikkel N. Schmidt, Massimo Buscema, et al.
(2024)
Open Access
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