UGC Approved Journal no 63975(19)

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

Volume 8 Issue 5
May-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2105170


Registration ID:
308943

Page Number

b307-b314

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Title

COVID-19 DETECTION USING X-RAY IMAGES

Abstract

The coronavirus 2019(COVID-19), which first occur in wuhan city of China in December 2019, spread quickly around the world and became a plague. It is necessary to detect the positive cases as early as possible so as to prevent the further spread of this disease. Application of convolutional neural networks (CNN) techniques coupled with medical imaging can be helpful for the accurate detection of this disease. In this project a new model for automated COVID-19 detection using raw chest X-ray images is used. The model is developed to supply accurate diagnosis for binary classification (COVID vs No-Findings). Our model produced an accuracy of 98.44%. The sequential model was used to train a model using Keras and Tensorflow. We introduced convolutional layers and implemented different filtering on each layer.

Key Words

Covid-19 detection, X- Ray Image & Disease

Cite This Article

"COVID-19 DETECTION USING X-RAY IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.b307-b314, May-2021, Available :http://www.jetir.org/papers/JETIR2105170.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

"COVID-19 DETECTION USING X-RAY IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppb307-b314, May-2021, Available at : http://www.jetir.org/papers/JETIR2105170.pdf

Publication Details

Published Paper ID: JETIR2105170
Registration ID: 308943
Published In: Volume 8 | Issue 5 | Year May-2021
DOI (Digital Object Identifier):
Page No: b307-b314
Country: Namakkal, Tamilnadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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