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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
ISSN Online 2393-8021ISSN Print 2394-1588Since 2014
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← Back to VOLUME 9, ISSUE 5, MAY 2022

DIAGNOSIS OF COVID-19 USING DEEP LEARNING TECHNIQUES

Vasupalli Chandini, ShaikAlthaf Rahaman

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Abstract: Early diagnosis of the corona virus disease in 2019(COVID-19) is essential for controlling this pandemic. COVID-19 has been circulating rapidly all over the world. There is no vaccine· accessible for this virus yet. Fast and detailed COVID-19 screening is possible using computed tomography (CT) scan images. The deep learning techniques used in the proposed method is based on a complexity neural network (CNN).We immediate on differentiating the CT scan images of COVID-19 and non-COVID 19 CT using different deep learning techniques. A self-developed model named CTnet-10 was designed for the COVID-19diagnosis, having an accuracy of 82.1%. The VGG-19 proved to be superior with an accuracy of 94.52% as analyse to all other deep learning models. Automatic diagnosis of COVID-19 from the CT scan pictures can be used by the doctors as a brisk and competent method for COVID-19 screening.

Keywords: COVID-19, CNN, CT scan, diagnosis, VGG, CTnet-10.

How to Cite:

[1] Vasupalli Chandini, ShaikAlthaf Rahaman, “DIAGNOSIS OF COVID-19 USING DEEP LEARNING TECHNIQUES,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2022.9534

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