Abstract

Novel coronavirus, known as COVID-19, is a very dangerous virus. Initially detected in China, it has since spread all over the world causing many deaths. There are several variants of COVID-19, which have been categorized into two major groups. These groups are variants of concern and variants of interest. Variants of concern are more dangerous, and there is a need to develop a system that can detect and classify COVID-19 and its variants without touching an infected person. In this paper, we propose a dual-stage-based deep learning framework to detect and classify COVID-19 and its variants. CT scans and chest X-ray images are used. Initially, the detection is done through a convolutional neural network, and then spatial features are extracted with deep convolutional models, while handcrafted features are extracted from several handcrafted descriptors. Both spatial and handcrafted features are combined to make a feature vector. This feature vector is called the vocabulary of features (VoF), as it contains spatial and handcrafted features. This feature vector is fed as an input to the classifier to classify different variants. The proposed model is evaluated based on accuracy, F1-score, specificity, sensitivity, specificity, Cohen’s kappa, and classification error. The experimental results show that the proposed method outperforms all the existing state-of-the-art methods.

Highlights

  • IntroductionChina in December 2019 and swiftly spread all over the world

  • Coronavirus, known as COVID-19, is a deadly virus that was discovered in WuhanChina in December 2019 and swiftly spread all over the world

  • The detection is done through a convolutional neural network, and spatial features are extracted with deep convolutional models, while handcrafted features are extracted from several handcrafted descriptors

Read more

Summary

Introduction

China in December 2019 and swiftly spread all over the world. The World Health Organization (WHO) called it a global pandemic [1]. It has several variants; these variants are categorized into three major groups, named as variants of concern, variants of interest, and variants under monitoring. Variants of concern can cause an increase in transmission. These variants are alpha (α), beta (β), gamma (γ) [2], and delta (δ) [3]. The variants of concern are more dangerous and cause death. These variants transmit from one individual to others due to physical contact. The most recent and dangerous variant of COVID-19 is the delta variant

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call