TELKOMNIKA Telecommunication, Computing, Electronics and Control
Classification of pneumonia from X-ray images using siamese convolutional network
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Classification of pneumonia from X-ray images using siamese convolutional network
Classification of pneumonia from X-ray images using siamese convolutional network
Subject
Chest X-Ray, Image classification, Pneumonia, Siamese Convolutional, Network
Description
Pneumonia is one of the highest global causes of deaths especially for children under 5 years old. This happened mainly because of the difficulties in identifying the cause of pneumonia. As a result, the treatment given may not be suitable for each pneumonia case. Recent studies have used deep learning approaches to obtain better classification within the cause of pneumonia. In this research, we used
siamese convolutional network (SCN) to classify chest x-ray pneumonia image into 3 classes, namely normal conditions, bacterial pneumonia, and viral pneumonia. Siamese convolutional network is a neural network architecture that learns similarity knowledge between pairs of image inputs based on the differences between its features. One of the important benefits of classifying data with SCN is the availability of comparable images that can be used as a reference when determining class. Using SCN, our best model achieved 80.03% accuracy, 79.59% f1 score, and an improved result reasoning by providing the comparable images.
siamese convolutional network (SCN) to classify chest x-ray pneumonia image into 3 classes, namely normal conditions, bacterial pneumonia, and viral pneumonia. Siamese convolutional network is a neural network architecture that learns similarity knowledge between pairs of image inputs based on the differences between its features. One of the important benefits of classifying data with SCN is the availability of comparable images that can be used as a reference when determining class. Using SCN, our best model achieved 80.03% accuracy, 79.59% f1 score, and an improved result reasoning by providing the comparable images.
Creator
Kennard Alcander Prayogo, Alethea Suryadibrata, Julio Christian Young
Source
DOI: 10.12928/TELKOMNIKA.v18i3.14751
Publisher
Universitas Ahmad Dahlan
Date
June 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Kennard Alcander Prayogo, Alethea Suryadibrata, Julio Christian Young, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Classification of pneumonia from X-ray images using siamese convolutional network,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/3830.
Classification of pneumonia from X-ray images using siamese convolutional network,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/3830.