UGC CARE norms ugc approved journal norms IJRTI Research Journal

Click Here

International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 8

Issue Published : 84

Article Submitted : 7748

Article Published : 3948

Total Authors : 10260

Total Reviewer : 547

Total Countries : 81

Indexing Partner


This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Authors Name: Ruchitha , Bindushree Shetty , Devashish Murthy K , Panduranga Nayak U , Prema Jain
Download E-Certificate: Download
Author Reg. ID:
Published Paper Id: IJRTI2210065
Published In: Volume 7 Issue 10, October-2022
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.
Cite Article: "DETECTION OF PNEUMONIA USING CNN", International Journal of Science & Engineering Development Research (, ISSN:2455-2631, Vol.7, Issue 10, page no.492 - 495, October-2022, Available :
Downloads: 000202409
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 :
Published Paper PDF:
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)

Providing A digital object identifier by DOI.ONE
How to Get DOI?


Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Join RMS/Earn 300


Indexing Partner