UGC Approved Journal no 63975(19)

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

Volume 8 Issue 10
October-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2110229


Registration ID:
315984

Page Number

c234-c243

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Title

Automation Detection Of COVID-19 Cases Using X-Ray Images

Abstract

Corona Virus continues to possess its effects on the people lives across the world. The screening of infected persons is vital step because it is a fast and low-cost way. Chest X- ray images plays a major crucial role and it is used for examination in detection of CORONA VIRUS(COVID-19). Here radiological chest X-rays are easily available with low cost only. In this survey paper, we are using a Convolutional Neural Network(CNN) based solution that will benefit in detection of the Covid-19 Positive patients using radiography chest X-Ray images. To test the efficiency of the solution, we are using public available X- Ray images of Corona Virus Positive cases and negative cases. Images of Positive Corona Virus patients and pictures of healthy person images are divided into testing images and trainable images. The solution which we are providing will give good results in classification accuracy within the test set-up. Here we are going to develop a GUI application for medical Examination areas. This GUI application can be used on any computer and performed by any medical examiner or technician to determine Corona Virus positive patients using radiography X-ray images. The result will be shown or provided by this application is really fast and done within a few seconds.

Key Words

Corona Virus, Deep Learning, CNN, Convolutional neural networks, Deep CNN, Detection.

Cite This Article

"Automation Detection Of COVID-19 Cases Using X-Ray Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.c234-c243, October-2021, Available :http://www.jetir.org/papers/JETIR2110229.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

"Automation Detection Of COVID-19 Cases 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 10, page no. ppc234-c243, October-2021, Available at : http://www.jetir.org/papers/JETIR2110229.pdf

Publication Details

Published Paper ID: JETIR2110229
Registration ID: 315984
Published In: Volume 8 | Issue 10 | Year October-2021
DOI (Digital Object Identifier):
Page No: c234-c243
Country: Kolar, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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