287 related articles for article (PubMed ID: 37765965)
1. Enhancing Cross-Subject Motor Imagery Classification in EEG-Based Brain-Computer Interfaces by Using Multi-Branch CNN.
Chowdhury RR; Muhammad Y; Adeel U
Sensors (Basel); 2023 Sep; 23(18):. PubMed ID: 37765965
[TBL] [Abstract][Full Text] [Related]
2. A Multibranch of Convolutional Neural Network Models for Electroencephalogram-Based Motor Imagery Classification.
Altuwaijri GA; Muhammad G
Biosensors (Basel); 2022 Jan; 12(1):. PubMed ID: 35049650
[TBL] [Abstract][Full Text] [Related]
3. Improving the performance of multisubject motor imagery-based BCIs using twin cascaded softmax CNNs.
Luo J; Shi W; Lu N; Wang J; Chen H; Wang Y; Lu X; Wang X; Hei X
J Neural Eng; 2021 Mar; 18(3):. PubMed ID: 33540387
[No Abstract] [Full Text] [Related]
4. EEG-FMCNN: A fusion multi-branch 1D convolutional neural network for EEG-based motor imagery classification.
Wang W; Li B; Wang H; Wang X; Qin Y; Shi X; Liu S
Med Biol Eng Comput; 2024 Jan; 62(1):107-120. PubMed ID: 37728715
[TBL] [Abstract][Full Text] [Related]
5. A robust multi-branch multi-attention-mechanism EEGNet for motor imagery BCI decoding.
Deng H; Li M; Li J; Guo M; Xu G
J Neurosci Methods; 2024 May; 405():110108. PubMed ID: 38458260
[TBL] [Abstract][Full Text] [Related]
6. Attention-based convolutional neural network with multi-modal temporal information fusion for motor imagery EEG decoding.
Ma X; Chen W; Pei Z; Zhang Y; Chen J
Comput Biol Med; 2024 Jun; 175():108504. PubMed ID: 38701593
[TBL] [Abstract][Full Text] [Related]
7. Multi-Domain Convolutional Neural Networks for Lower-Limb Motor Imagery Using Dry vs. Wet Electrodes.
Jeong JH; Choi JH; Kim KT; Lee SJ; Kim DJ; Kim HM
Sensors (Basel); 2021 Oct; 21(19):. PubMed ID: 34640992
[TBL] [Abstract][Full Text] [Related]
8. EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces.
Lawhern VJ; Solon AJ; Waytowich NR; Gordon SM; Hung CP; Lance BJ
J Neural Eng; 2018 Oct; 15(5):056013. PubMed ID: 29932424
[TBL] [Abstract][Full Text] [Related]
9. A Combined Virtual Electrode-Based ESA and CNN Method for MI-EEG Signal Feature Extraction and Classification.
Lun X; Zhang Y; Zhu M; Lian Y; Hou Y
Sensors (Basel); 2023 Nov; 23(21):. PubMed ID: 37960592
[TBL] [Abstract][Full Text] [Related]
10. Optimal Channel Selection of Multiclass Motor Imagery Classification Based on Fusion Convolutional Neural Network with Attention Blocks.
Khabti J; AlAhmadi S; Soudani A
Sensors (Basel); 2024 May; 24(10):. PubMed ID: 38794022
[TBL] [Abstract][Full Text] [Related]
11. A multiscale siamese convolutional neural network with cross-channel fusion for motor imagery decoding.
Shen L; Xia Y; Li Y; Sun M
J Neurosci Methods; 2022 Feb; 367():109426. PubMed ID: 34902364
[TBL] [Abstract][Full Text] [Related]
12. EEG-inception: an accurate and robust end-to-end neural network for EEG-based motor imagery classification.
Zhang C; Kim YK; Eskandarian A
J Neural Eng; 2021 Mar; 18(4):. PubMed ID: 33691299
[No Abstract] [Full Text] [Related]
13. Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals.
Tayeb Z; Fedjaev J; Ghaboosi N; Richter C; Everding L; Qu X; Wu Y; Cheng G; Conradt J
Sensors (Basel); 2019 Jan; 19(1):. PubMed ID: 30626132
[TBL] [Abstract][Full Text] [Related]
14. A Multi-Branch Convolutional Neural Network with Squeeze-and-Excitation Attention Blocks for EEG-Based Motor Imagery Signals Classification.
Altuwaijri GA; Muhammad G; Altaheri H; Alsulaiman M
Diagnostics (Basel); 2022 Apr; 12(4):. PubMed ID: 35454043
[TBL] [Abstract][Full Text] [Related]
15. Bidirectional feature pyramid attention-based temporal convolutional network model for motor imagery electroencephalogram classification.
Xie X; Chen L; Qin S; Zha F; Fan X
Front Neurorobot; 2024; 18():1343249. PubMed ID: 38352723
[TBL] [Abstract][Full Text] [Related]
16. Motor Imagery EEG Classification Using Capsule Networks.
Ha KW; Jeong JW
Sensors (Basel); 2019 Jun; 19(13):. PubMed ID: 31252557
[TBL] [Abstract][Full Text] [Related]
17. Imagined character recognition through EEG signals using deep convolutional neural network.
Ullah S; Halim Z
Med Biol Eng Comput; 2021 May; 59(5):1167-1183. PubMed ID: 33945075
[TBL] [Abstract][Full Text] [Related]
18. An Ensemble CNN for Subject-Independent Classification of Motor Imagery-based EEG.
Dolzhikova I; Abibullaev B; Sameni R; Zollanvari A
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():319-324. PubMed ID: 34891300
[TBL] [Abstract][Full Text] [Related]
19. Golden subject is everyone: A subject transfer neural network for motor imagery-based brain computer interfaces.
Sun B; Wu Z; Hu Y; Li T
Neural Netw; 2022 Jul; 151():111-120. PubMed ID: 35405471
[TBL] [Abstract][Full Text] [Related]
20. Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.
Park D; Park H; Kim S; Choo S; Lee S; Nam CS; Jung JY
IEEE Trans Neural Syst Rehabil Eng; 2023; 31():4504-4513. PubMed ID: 37934650
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
