Conference Papers

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Author: search.filters.author.Azade, A.Subject: search.filters.subject.Deep Learning

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    Impact of Image Augmentation in COVID-19 Detection Using Chest X-Ray Images
    (Institute of Electrical and Electronics Engineers Inc., 2022) Azade, A.; Anand Kumar, M.
    COVID-19 continues to have a devastating impact on people's lives worldwide. In order to combat this condition, it is critical to test affected people in a timely and cost-effective manner. Radiological examination is one of the most efficient ways to attain this goal, with the most widely available and least expensive alternative being a CXR. The artificial intelligence and data science communities have aided in the global response to COVID-19, a novel coronavirus. Detection and diagnosis techniques have focused on developing rapid diagnostic approaches based on chest X-rays and deep learning. In this paper, we have analyzed the impact of augmentation in COVID-19 CXR images with normal lung opacity and viral pneumonia images and presented a model for the detection of COVID-19. © 2022 IEEE.