Automatic Detection of COVID-19 Using Ensemble Transfer Learning Based on Lung CT Scans

Ricardo Pillay, Serestina Viriri, Reolyn Heymann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to curb the rapid spread of COVID-19, early and accurate detection is required. Computer Tomography (CT) scans of the lungs can be utilized for accurate COVID-19 detection because these medical images highlight COVID-19 infection with high sensitivity. Transfer learning was implemented on six state-of-the-art Convolutional Neural Networks (CNNs). From these six CNNs, the three with the highest accuracies (based on empirical experiments) were selected and used as base learners to produce hard voting and soft voting ensemble classifiers. These three CNNs were identified as Vgg16, EfficientNetB0 and EfficientNetB5. This study concludes that the soft voting ensemble classifier, with base learners Vgg16 and EfficientNetB5, outperformed all other ensemble classifiers with different base learners and individual models that were investigated. The proposed classifier achieved a new state-of-the-art accuracy on the SARS-CoV-2 dataset. The accuracy obtained from this framework was 98.13%, the recall was 98.94%, the precision was 97.40%, the specificity was 97.30% and the F1 score was 98.16%.

Original languageEnglish
Title of host publicationPan-African Artificial Intelligence and Smart Systems - Second EAI International Conference, PAAISS 2022, Proceedings
EditorsTelex Magloire Ngatched Nkouatchah, Isaac Woungang, Jules-Raymond Tapamo, Serestina Viriri
PublisherSpringer Science and Business Media Deutschland GmbH
Pages181-204
Number of pages24
ISBN (Print)9783031252709
DOIs
Publication statusPublished - 2023
Event2nd International Conference on Pan-African Intelligence and Smart Systems, PAAISS 2022 - Dakar, Senegal
Duration: 2 Nov 20224 Nov 2022

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume459 LNICST
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X

Conference

Conference2nd International Conference on Pan-African Intelligence and Smart Systems, PAAISS 2022
Country/TerritorySenegal
CityDakar
Period2/11/224/11/22

Keywords

  • Convolutional neural network
  • Deep learning
  • Hard voting
  • Soft voting
  • Transfer learning

ASJC Scopus subject areas

  • Computer Networks and Communications

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