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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 8

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Paper Title: DETECTION OF PNEUMONIA USING CNN
Authors Name: Ruchitha , Bindushree Shetty , Devashish Murthy K , Panduranga Nayak U , Prema Jain
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IJRTI_183018
Published Paper Id: IJRTI2210065
Published In: Volume 7 Issue 10, October-2022
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Abstract: Pneumonia is one of the diseases that people may additionally come across in any length in their lives. approximately 18% of infectious illnesses are caused by pneumonia. Pneumonia may additionally bring about loss of life within the following tiers. for you to diagnose pneumonia as a scientific circumstance, lung X-ray pics are robotically tested through the sector professionals inside the scientific practice. in this take a look at, lung X-ray images which can be to be had for the analysis of pneumonia were used. The convolutional neural network was hired as characteristic extractor, and a number of present convolutional neural community models together with, VGG-16 and VGG-19 were applied so that you can realize this precise assignment. Then, the number of deep functions changed into decreased from 1000 to 100 through using the minimum redundancy most relevance algorithm for each deep version. accordingly, we carried out a hundred deep features from every deep version, and we combined these functions a good way to offer an efficient characteristic set consisting of totally three hundred deep capabilities. in this step of the experiment, this selection set become given as an enter to the choice tree, ok-nearest neighbours, linear discriminant evaluation, linear regression, and aid vector device studying fashions. eventually, all models ensured promising consequences, mainly linear discriminant evaluation yielded the maximum efficient consequences with an accuracy of 95.36%. consequently, the outcomes point out that the deep functions supplied sturdy and consistent features for pneumonia detection, and minimum redundancy maximum relevance method turned into discovered a beneficial device to reduce the size of the characteristic set.
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Cite Article: "DETECTION OF PNEUMONIA USING CNN", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 10, page no.492 - 495, October-2022, Available :http://www.ijrti.org/papers/IJRTI2210065.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2210065
Registration ID:183018
Published In: Volume 7 Issue 10, October-2022
DOI (Digital Object Identifier):
Page No: 492 - 495
Country: Dakshina Kannada, Karnataka, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2210065
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2210065
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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