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1 Ergebnisse
1
SAT-Net: SincNet-Based Attentive Temporal Convolutional Net..:
, In:
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
,
Kim, Jun-Mo
;
Bak, Soyeon
;
Nam, Hyeonyeong
... - p. 4452-4457 , 2023
Link:
https://doi.org/10.1109/SMC53992.2023.10393906
RT T1 <cTitle>2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)</cTitle>: T1 <Title>SAT-Net: SincNet-Based Attentive Temporal Convolutional Network for Motor Imagery Classification</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10393906&Exemplar=1&LAN=DE A1 Kim, Jun-Mo A1 Bak, Soyeon A1 Nam, Hyeonyeong A1 Choi, WooHyeok A1 Kim, Da-Hyun A1 Kam, Tae-Eui YR 2023 SN 2577-1655 K1 Band-pass filters K1 Deep learning K1 Convolution K1 Statistical analysis K1 Feature extraction K1 Information filters K1 Electroencephalography K1 Brain-computer Interface K1 Electroencephalogra-phy K1 Motor Imagery K1 SincNet K1 Temporal Convolutional Network SP 4452 OP 4457 LK http://dx.doi.org/https://doi.org/10.1109/SMC53992.2023.10393906 DO https://doi.org/10.1109/SMC53992.2023.10393906 SF ELIB - SuUB Bremen
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