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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Deep Learning and Classification Algorithms for COVID-19 Detection

Author 1: Mohammed Sidheeque
Author 2: P. Sumathy
Author 3: Abdul Gafur. M

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130940

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 9, 2022.

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Abstract: The imaging modalities of chest X-rays and computed tomography (CT) are commonly utilized to quickly and accurately diagnose COVID-19. Due to time and human error, it is exceedingly difficult to manually identify the infection using radio imaging. COVID-19 identification is being mechanized and improved with the use of artificial intelligence (AI) tools that have already showed promise. This study employs the following methodology: The chest footage was pre-processed by setting equalizing the histogram, sharpening it, and so on. The transformed chest images are then retrieved through shallow and high-level feature mapping over the backbone network. To further improve the classification performance of the convolutional neural network, the model uses self-attained mechanism through feature maps. Numerous simulations show that CT image classification and augmentation may be accomplished with higher efficiency and flexibility using the Inception-Resnet convolutional neural network than with traditional segmentation methods. The experiment illustrates the association between model accuracy, model loss, and epoch. Inception-statistical Resnet's measurement results are 98%, 91%, 91%.

Keywords: Deep Learning; COVID-19; classification; artificial intelligence

Mohammed Sidheeque, P. Sumathy and Abdul Gafur. M, “Deep Learning and Classification Algorithms for COVID-19 Detection” International Journal of Advanced Computer Science and Applications(IJACSA), 13(9), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130940

@article{Sidheeque2022,
title = {Deep Learning and Classification Algorithms for COVID-19 Detection},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130940},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130940},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {9},
author = {Mohammed Sidheeque and P. Sumathy and Abdul Gafur. M}
}


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