Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images

Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images

Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets, networks generalize poorly. Data Augmentation techniques improve the generalizability of neural networks by using existing training data more effectively. Standard data augmentatio...

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Bibliographic Details
Main Authors: Saman Motamed, Patrik Rogalla, Farzad Khalvati
Format: article
Language:EN
Published: Elsevier 2021
Subjects:
Data augmentation
Semi-supervised learning
Generative adversarial networks
Disease detection
Medical Imaging
Computer applications to medicine. Medical informatics
R858-859.7
Online Access:https://doaj.org/article/5840f55202eb42e8ad8690506a751581
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https://doaj.org/article/5840f55202eb42e8ad8690506a751581

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