학술논문
Classification of Pulmonary Viruses X-ray and Detection of COVID-19 Based on Invariant of Inception-V 3 Deep Learning Model
Document Type
Conference
Source
2021 International Conference on Computing, Electronic and Electrical Engineering (ICE Cube) Computing, Electronic and Electrical Engineering (ICE Cube), 2021 International Conference on. :1-6 Oct, 2021
Subject
Language
Abstract
Coronavirus (COVID-19) is a catastrophic illness that has already infected several million individuals and caused thousands of fatalities globally. Any technical technique that enables quick testing of the COVID-19 with high accuracy might be essential for healthcare providers. X-ray imaging is an easily available technique that might be a great option for its quick detection. This research was conducted to examine the usefulness of artificial intelligence (AI) to detect COVID-19 quickly and accurately from chest X-ray scans. The objective of this study is to provide a solid technical method for the automatic identification of COVID-19, Pneumonia, Lung opacity, and Normal digital X-ray scans using pretrained, deep learning algorithms while optimizing detection accuracy. Inception v3 with an additional added dense layer is used with image augmentation to train and validate the selected dataset. The obtained accuracy of 99.72% promises speedy detection of COVID-19.