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TOINet: Transfer Learning from Overt Speech- to Imagined Sp..:
, In:
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
,
Lee, Dae-Hyeok
;
Kim, Sung-Jin
;
Han, Hyeon-Taek
. - p. 4441-4446 , 2023
Link:
https://doi.org/10.1109/SMC53992.2023.10394004
RT T1 <cTitle>2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)</cTitle>: T1 <Title>TOINet: Transfer Learning from Overt Speech- to Imagined Speech-Based EEG Signals with Convolutional Autoencoder</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10394004&Exemplar=1&LAN=DE A1 Lee, Dae-Hyeok A1 Kim, Sung-Jin A1 Han, Hyeon-Taek A1 Lee, Seong-Whan YR 2023 SN 2577-1655 K1 Learning systems K1 Transfer learning K1 Feature extraction K1 Brain modeling K1 Speech K1 Electroencephalography K1 Brain-computer interfaces K1 Brain-computer interface (BCI) K1 Electroen-cephalogram (EEG) K1 Imagined speech K1 Deep autoencoder SP 4441 OP 4446 LK http://dx.doi.org/https://doi.org/10.1109/SMC53992.2023.10394004 DO https://doi.org/10.1109/SMC53992.2023.10394004 SF ELIB - SuUB Bremen
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