196 related articles for article (PubMed ID: 35368726)
1. Depression Assessment Method: An EEG Emotion Recognition Framework Based on Spatiotemporal Neural Network.
Chang H; Zong Y; Zheng W; Tang C; Zhu J; Li X
Front Psychiatry; 2021; 12():837149. PubMed ID: 35368726
[TBL] [Abstract][Full Text] [Related]
2. Electroencephalogram signals emotion recognition based on convolutional neural network-recurrent neural network framework with channel-temporal attention mechanism for older adults.
Jiang L; Siriaraya P; Choi D; Zeng F; Kuwahara N
Front Aging Neurosci; 2022; 14():945024. PubMed ID: 36212045
[TBL] [Abstract][Full Text] [Related]
3. Spatial-frequency-temporal convolutional recurrent network for olfactory-enhanced EEG emotion recognition.
Xing M; Hu S; Wei B; Lv Z
J Neurosci Methods; 2022 Jul; 376():109624. PubMed ID: 35588948
[TBL] [Abstract][Full Text] [Related]
4. CDBA: a novel multi-branch feature fusion model for EEG-based emotion recognition.
Huang Z; Ma Y; Su J; Shi H; Jia S; Yuan B; Li W; Geng J; Yang T
Front Physiol; 2023; 14():1200656. PubMed ID: 37546532
[TBL] [Abstract][Full Text] [Related]
5. EEG-based emotion charting for Parkinson's disease patients using Convolutional Recurrent Neural Networks and cross dataset learning.
Dar MN; Akram MU; Yuvaraj R; Gul Khawaja S; Murugappan M
Comput Biol Med; 2022 May; 144():105327. PubMed ID: 35303579
[TBL] [Abstract][Full Text] [Related]
6. Spatial-temporal features-based EEG emotion recognition using graph convolution network and long short-term memory.
Zheng F; Hu B; Zheng X; Zhang Y
Physiol Meas; 2023 Jun; 44(6):. PubMed ID: 37196649
[No Abstract] [Full Text] [Related]
7. Emotion recognition using spatial-temporal EEG features through convolutional graph attention network.
Li Z; Zhang G; Wang L; Wei J; Dang J
J Neural Eng; 2023 Feb; 20(1):. PubMed ID: 36720164
[No Abstract] [Full Text] [Related]
8. Investigating the Use of Pretrained Convolutional Neural Network on Cross-Subject and Cross-Dataset EEG Emotion Recognition.
Cimtay Y; Ekmekcioglu E
Sensors (Basel); 2020 Apr; 20(7):. PubMed ID: 32260445
[TBL] [Abstract][Full Text] [Related]
9. Multidimensional Feature in Emotion Recognition Based on Multi-Channel EEG Signals.
Li Q; Liu Y; Liu Q; Zhang Q; Yan F; Ma Y; Zhang X
Entropy (Basel); 2022 Dec; 24(12):. PubMed ID: 36554234
[TBL] [Abstract][Full Text] [Related]
10. Attention-based 3D convolutional recurrent neural network model for multimodal emotion recognition.
Du Y; Li P; Cheng L; Zhang X; Li M; Li F
Front Neurosci; 2023; 17():1330077. PubMed ID: 38268710
[TBL] [Abstract][Full Text] [Related]
11. Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals.
Maheshwari D; Ghosh SK; Tripathy RK; Sharma M; Acharya UR
Comput Biol Med; 2021 Jul; 134():104428. PubMed ID: 33984749
[TBL] [Abstract][Full Text] [Related]
12. 3DCANN: A Spatio-Temporal Convolution Attention Neural Network for EEG Emotion Recognition.
Liu S; Wang X; Zhao L; Li B; Hu W; Yu J; Zhang YD
IEEE J Biomed Health Inform; 2022 Nov; 26(11):5321-5331. PubMed ID: 34033551
[TBL] [Abstract][Full Text] [Related]
13. EEG Emotion Recognition Network Based on Attention and Spatiotemporal Convolution.
Zhu X; Liu C; Zhao L; Wang S
Sensors (Basel); 2024 May; 24(11):. PubMed ID: 38894254
[TBL] [Abstract][Full Text] [Related]
14. EEG-based emotion recognition using 4D convolutional recurrent neural network.
Shen F; Dai G; Lin G; Zhang J; Kong W; Zeng H
Cogn Neurodyn; 2020 Dec; 14(6):815-828. PubMed ID: 33101533
[TBL] [Abstract][Full Text] [Related]
15. Accelerating 3D Convolutional Neural Network with Channel Bottleneck Module for EEG-Based Emotion Recognition.
Kim S; Kim TS; Lee WH
Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146160
[TBL] [Abstract][Full Text] [Related]
16. EEG-Based Emotion Recognition Using Spatial-Temporal Graph Convolutional LSTM With Attention Mechanism.
Feng L; Cheng C; Zhao M; Deng H; Zhang Y
IEEE J Biomed Health Inform; 2022 Nov; 26(11):5406-5417. PubMed ID: 35969553
[TBL] [Abstract][Full Text] [Related]
17. S-LSTM-ATT: a hybrid deep learning approach with optimized features for emotion recognition in electroencephalogram.
Abgeena A; Garg S
Health Inf Sci Syst; 2023 Dec; 11(1):40. PubMed ID: 37654692
[TBL] [Abstract][Full Text] [Related]
18. The multiscale 3D convolutional network for emotion recognition based on electroencephalogram.
Su Y; Zhang Z; Li X; Zhang B; Ma H
Front Neurosci; 2022; 16():872311. PubMed ID: 36046470
[TBL] [Abstract][Full Text] [Related]
19. LSTM-enhanced multi-view dynamical emotion graph representation for EEG signal recognition.
Xu G; Guo W; Wang Y
J Neural Eng; 2023 Jun; 20(3):. PubMed ID: 37343566
[No Abstract] [Full Text] [Related]
20. Subject-Independent Emotion Recognition of EEG Signals Based on Dynamic Empirical Convolutional Neural Network.
Liu S; Wang X; Zhao L; Zhao J; Xin Q; Wang SH
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(5):1710-1721. PubMed ID: 32833640
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]