Deep Fractional Max Pooling Neural Network for COVID-19 Recognition

Aim: Coronavirus disease 2019 (COVID-19) is a form of disease triggered by a new strain of coronavirus. This paper proposes a novel model termed “deep fractional max pooling neural network (DFMPNN)” to diagnose COVID-19 more efficiently. Methods: This 12-layer DFMPNN replaces max pooling (MP) and av...

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Detalles Bibliográficos
Autores principales: Wang, Shui-Hua, Satapathy, Suresh Chandra, Anderson, Donovan, Chen, Shi-Xin, Zhang, Yu-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Public Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8383320/
https://www.ncbi.nlm.nih.gov/pubmed/34447739
http://dx.doi.org/10.3389/fpubh.2021.726144

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8383320/
https://www.ncbi.nlm.nih.gov/pubmed/34447739
http://dx.doi.org/10.3389/fpubh.2021.726144

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