Five deep dearning models for classification of chest X-ray images of COVID-19

Simple item page
dc.contributor.authorFerdi, Abdesselam
dc.contributor.authorBenierbah, Said
dc.contributor.authorFerdi, Youcef
dc.date.accessioned2025-04-17T22:42:05Z
dc.date.available2025-04-17T22:42:05Z
dc.date.issued2021
dc.description.abstractIn recent years, deep learning algorithms have acquired a great popularity in many fields including medical imaging to achieve different tasks such as image segmenta-tion, classification, detection, and retrieval tasks. Although reverse transcription po-lymerase chain reaction test (RT-PCR) is considered to be the gold standard for CO-VID- 19 screening, deep learning algorithms may help radiologists to automatically diagnose this disease by processing chest Xray (CXR) and chest CT images. This paper proposes a comparative study of five deep learning models for classification of CXR COVID-19 images. The five selected models are pre-trained networks, namely, ResNet-50, InceptionResNet-v2, Inception-v3, MobileNet-v2, and GoogleNet. The models were evaluated using CXR COVID-19 and normal images from publicly avail-able datasets. The obtained classification results show that the GoogleNet model achieves the highest classification performance with a validation accuracy of 95.69%.
dc.identifier.urihttp://dspace.univ-oeb.dz:4000/handle/123456789/21900
dc.language.isoen
dc.publisherUniversity of Oum El Bouaghi
dc.subjectCOVID-19 ; Deep Learning ; Convolutional Network ; Chest X-ray image ; Medical Image Processing
dc.titleFive deep dearning models for classification of chest X-ray images of COVID-19
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Five Deep Learning Models for Classification of.pdf
Size:
600.88 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
The 1 ST international conference on electronics, artificial intelligence and technologies ICEAINT 2021