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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 7, JULY 2021

“Pneumonia Detection Using Deep Learning”

Divyashree P, Priya Srinivasa, Nishanth Verma

DOI: 10.17148/IJARCCE.2021.10747

Abstract: This project prioritizes a convolutional neural network model that has been trained to differentiate and detect pneumonia from X-ray image samples. Unlike other procedures that relay on learning methods of transmission or traditional hand-crafted procedures for obtaining different isolation functions, the convolutional neural network model from scratch to extract features from a given X-ray chest image and isolate to determine whether a person has pneumonia or not. This model can help reduce the reliability and accountability challenges they face when dealing with medical imaging.

Keywords: Convolutional Neural Network (CNN), World Health Organization (WHO), artificial neural network (ANN), Artificial neural network, CheXNet algorithm.

How to Cite:

[1] Divyashree P, Priya Srinivasa, Nishanth Verma, ““Pneumonia Detection Using Deep Learning”,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.10747