#5822. Deep transfer learning based classification model for covid-19 using chest CT-scans

July 2026publication date
Proposal available till 15-05-2025
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Journal’s subject area:
Signal Processing;
Software;
Computer Vision and Pattern Recognition;
Artificial Intelligence;
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Abstract:
COVID-19 is an infectious and contagious virus. As of this writing, more than 160 million people have been infected since its emergence, including more than 125,000 in Algeria. In this work, We first collected a dataset of 4986 COVID and non-COVID images confirmed by RT-PCR tests at Tlemcen hospital in Algeria. Then we performed a transfer learning on deep learning models that got the best results on the ImageNet dataset, such as DenseNet121, DenseNet201, VGG16, VGG19, Inception Resnet-V2, and Xception, in order to conduct a comparative study. Therefore, We have proposed an explainable model based on the DenseNet201 architecture and the GradCam explanation algorithm to detect COVID-19 in chest CT images and explain the output decision.
Keywords:
COVID-19; Densenet-121; Densenet-201; Imagenet; Xception

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