EEG-CDILNet: a lightweight and accurate CNN network using circular dilated convolution for motor imagery classification.

Liang, Tie; Yu, Xionghui; Liu, Xiaoguang; Wang, Hongrui; Liu, Xiuling; Dong, Bin

Liang, Tie; Yu, Xionghui; Liu, Xiaoguang; Wang, Hongrui; Liu, Xiuling; Dong, Bin.

Afiliación

Liang T; Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding 071002, People's Republic of China.
Yu X; College of Electronic Information Engineering, Hebei University, Baoding 071002, People's Republic of China.
Liu X; Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding 071002, People's Republic of China.
Wang H; College of Electronic Information Engineering, Hebei University, Baoding 071002, People's Republic of China.
Liu X; Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding 071002, People's Republic of China.
Dong B; College of Electronic Information Engineering, Hebei University, Baoding 071002, People's Republic of China.

J Neural Eng ; 20(4)2023 08 21.

Article en En | MEDLINE | ID: mdl-37552978

Asunto(s)

Algoritmos; Interfaces Cerebro-Computador; Movimiento; Redes Neurales de la Computación; Electroencefalografía/métodos; Imaginación

Palabras clave

convolutional neural networks (CNN); electroencephalography (EEG); lightweight network; motor imagery (MI)

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Interfaces Cerebro-Computador Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido

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