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 ave...
Main Authors: | Shui-Hua Wang, Suresh Chandra Satapathy, Donovan Anderson, Shi-Xin Chen, Yu-Dong Zhang |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-08-01
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Series: | Frontiers in Public Health |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2021.726144/full |
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