An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints

In image classification with Deep Convolutional Neural Networks (DCNNs), the number of parameters in pointwise convolutions rapidly grows due to the multiplication of the number of filters by the number of input channels that come from the previous layer. Existing studies demonstrated that a subnetw...

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Detalles Bibliográficos
Autores principales: Schwarz Schuler, Joao Paulo, Also, Santiago Romani, Puig, Domenec, Rashwan, Hatem, Abdel-Nasser, Mohamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497893/
https://www.ncbi.nlm.nih.gov/pubmed/36141151
http://dx.doi.org/10.3390/e24091264

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497893/
https://www.ncbi.nlm.nih.gov/pubmed/36141151
http://dx.doi.org/10.3390/e24091264

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