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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 11, ISSUE 8, AUGUST 2022

Importance of Capsule Network in detection of Lung Diseases

Poonam A. Rajput, Dr. Sanjay Buch

DOI: 10.17148/IJARCCE.2022.11811

Abstract: Lung Diseases is the most compelling research talking point in recent years. although a lot of research has been done on this subject still this field is arduous and confusing and There are numerous techniques to classify medical images. Deep learning techniques have achieved an magnificent result in the field of Medical Engineering and computer vision. One of the current disadvantages of pneumonia detection is it requires high- elucidate data sets. Convolution Neural Network requires lots of training data and not equipped to recognize pose and distortion of object, Due to these reasons Capsule Network is introduced. After reviewing the topic, this paper presents the advantages of capsule network over convolutional neural network and architecture of capsule network.

Keywords: Lung Diseases Detection, Chest X-ray images,CNN,Capsule Network

How to Cite:

[1] Poonam A. Rajput, Dr. Sanjay Buch, “Importance of Capsule Network in detection of Lung Diseases,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.11811