Multi-Kernel Temporal and Spatial Convolution for EEG-Based Emotion Classification

Deep learning using an end-to-end convolutional neural network (ConvNet) has been applied to several electroencephalography (EEG)-based brain–computer interface tasks to extract feature maps and classify the target output. However, the EEG analysis remains challenging since it requires consideration...

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Detalles Bibliográficos
Autores principales: Emsawas, Taweesak, Morita, Takashi, Kimura, Tsukasa, Fukui, Ken-ichi, Numao, Masayuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654218/
https://www.ncbi.nlm.nih.gov/pubmed/36365948
http://dx.doi.org/10.3390/s22218250

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654218/
https://www.ncbi.nlm.nih.gov/pubmed/36365948
http://dx.doi.org/10.3390/s22218250

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