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...

Full description

Bibliographic Details
Main Authors: Saman Motamed, Patrik Rogalla, Farzad Khalvati
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Data augmentation
Semi-supervised learning
Generative adversarial networks
Disease detection
Medical Imaging
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914821002501

Internet

http://www.sciencedirect.com/science/article/pii/S2352914821002501

Similar Items