Research and Verification of Convolutional Neural Network Lightweight in BCI

With the increasing of depth and complexity of the convolutional neural network, parameter dimensionality and volume of computing have greatly restricted its applications. Based on the SqueezeNet network structure, this study introduces a block convolution and uses channel shuffle between blocks to...

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Detalles Bibliográficos
Autores principales: Xu, Shipu, Li, Runlong, Wang, Yunsheng, Liu, Yong, Hu, Wenwen, Wu, Yingjing, Zhang, Chenxi, Liu, Chang, Ma, Chao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416271/
https://www.ncbi.nlm.nih.gov/pubmed/32802151
http://dx.doi.org/10.1155/2020/5916818

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416271/
https://www.ncbi.nlm.nih.gov/pubmed/32802151
http://dx.doi.org/10.1155/2020/5916818

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