UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 7
July-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2107204


Registration ID:
312100

Page Number

b607-b612

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Title

DEEP LEARNING BASED CORONA DETECTION SYSTEM USING X-RAY & CT SCAN

Abstract

Recently, the maximum spread disruption, which is the now infected Covid-19 contamination, has ceased to be effective. Because of this disorder, both humans and animals become inflamed. Every day people's lifestyles and their health as well as a farmer's financial system are affected as Covid-19 is currently a disorder that is spreading in a completely everyday place, and until now, and the vaccine against COVID-19 is no longer organized, Not even a single United States of America can prepare itself anymore. Observation of inflamed Corona Virus infected people has shown that all these kind of patients are firstly inflamed with lung contamination after exposure to the disorder. Chest x-rays and chest CT are powerful imaging techniques for identifying problems connected to lunge. However chest x-rays is cheaper than a chest Computed Tomography. Deep learning one of the accurate and successful system for gaining knowledge of the technology and has advantages. All analyzes to examine a large number of chest x-rays, which can have a good influence on the detection of corona. In these paintings we include the PA view of chest x-rays for patients affected by the corona virus as well as healthy patients. After we cleaned up the image and applied the information enhancement, we used a thorough understanding of the fully CNN-based fashion and its performance in comparison. We compare the modes of Inception V3, VGG-16 and test their accuracy. To examine version performance, a thousand chest X-rays example images were gathered from the GitHub repositories and Kaggle, 800 of which were used for schooling and 200 for validation. When analyzing the final results, the Inception version offers the best precision (i.e. 96.00%) for the detection of X-ray images in the chest compared to different modes.

Key Words

Deep Learning, Machine Learning, Chest X-ray images, Radiology images, DarkNet, Machine Learning, Deep Learning, Inception V3, VGG-16.

Cite This Article

"DEEP LEARNING BASED CORONA DETECTION SYSTEM USING X-RAY & CT SCAN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.b607-b612, July-2021, Available :http://www.jetir.org/papers/JETIR2107204.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"DEEP LEARNING BASED CORONA DETECTION SYSTEM USING X-RAY & CT SCAN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppb607-b612, July-2021, Available at : http://www.jetir.org/papers/JETIR2107204.pdf

Publication Details

Published Paper ID: JETIR2107204
Registration ID: 312100
Published In: Volume 8 | Issue 7 | Year July-2021
DOI (Digital Object Identifier):
Page No: b607-b612
Country: Nagpur, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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