Restructuring ResNet50 to Diagnose COVID-19

Abdulkader Helwan

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17 Feb 2021CPOL2 min read

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In this article, we’ll work on restructuring ResNet50 to perform the new classification task.

Here we’ll make this base model fit a new classification task: COVID-19 and Normal chest X-rays. We’ll use the ResNet50 model with a dataset that contains 2,484 images – a small dataset compared to ImageNet.

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This article is part of the series 'COVID-19 Diagnosis with Deep Learning ◁ Prev View All Next ▷

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Abdulkader Helwan

Engineer

Lebanon

Dr. Helwan is a machine learning and medical image analysis enthusiast.

His research interests include but not limited to Machine and deep learning in medicine, Medical computational intelligence, Biomedical image processing, and Biomedical engineering and systems.

Restructuring ResNet50 to Diagnose COVID-19

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