The Effectiveness of Image Augmentation in Deep Learning Networks for Detecting COVID-19: A Geometric Transformation Perspective

The Effectiveness of Image Augmentation in Deep Learning Networks for Detecting COVID-19: A Geometric Transformation Perspective

Chest X-ray imaging technology used for the early detection and screening of COVID-19 pneumonia is both accessible worldwide and affordable compared to other non-invasive technologies. Additionally, deep learning methods have recently shown remarkable results in detecting COVID-19 on chest X-rays, m...

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Bibliographic Details
Main Authors: Elgendi, Mohamed (Author), Nasir, Muhammad Umer (Author), Tang, Qunfeng (Author), Smith, David (Author), Grenier, John-Paul (Author), Batte, Catherine (Author), Spieler, Bradley (Author), Leslie, William Donald (Author), Menon, Carlo (Author), Fletcher, Richard R (Author), Howard, Newton (Author), Ward, Rabab (Author), Parker, William (Author), Nicolaou, Savvas (Author)
Other Authors: Massachusetts Institute of Technology. Department of Urban Studies and Planning (Contributor), Massachusetts Institute of Technology. Device Research Laboratory (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
Format: Article
Language:English
Published: Frontiers Media SA, 2021-03-22T22:39:31Z.
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