Reliable Learning with PDE-Based CNNs and DenseNets for Detecting COVID-19, Pneumonia, and Tuberculosis from Chest X-Ray Images

Reliable Learning with PDE-Based CNNs and DenseNets for Detecting COVID-19, Pneumonia, and Tuberculosis from Chest X-Ray Images

It has recently been shown that the interpretation by partial differential equations (PDEs) of a class of convolutional neural networks (CNNs) supports definition of architectures such as parabolic and hyperbolic networks. These networks have provable properties regarding the stability against the p...

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Bibliographic Details
Main Authors: Anca Nicoleta Marginean, Delia Doris Muntean, George Adrian Muntean, Adelina Priscu, Adrian Groza, Radu Razvan Slavescu, Calin Lucian Timbus, Gabriel Zeno Munteanu, Cezar Octavian Morosanu, Maria Margareta Cosnarovici, Camelia-M. Pintea
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Mathematics
Subjects:
partial differential equations (PDEs)
COVID-19
convolutional neural network (CNN)
imbalanced dataset
Online Access:https://www.mdpi.com/2227-7390/9/4/434

Internet

https://www.mdpi.com/2227-7390/9/4/434

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