Author: Jiang, Juntao; Lin, Shuyi
Title: COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer Cord-id: lu4rgiz1 Document date: 2021_10_16
ID: lu4rgiz1
Snippet: The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damages. Chest X-ray images are widely used for COVID-19 diagnosis and Artificial Intelligence method can assist to increase the efficiency and accuracy. In the Challenge of Chest XR COVID-19 detection in Ethics and Explainability for Responsible Data Science (EE-RDS) conference 2021, we proposed a method which combined Swin Transformer and Transformer in Transformer to classify chest X-ray images as three classes: CO
Document: The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damages. Chest X-ray images are widely used for COVID-19 diagnosis and Artificial Intelligence method can assist to increase the efficiency and accuracy. In the Challenge of Chest XR COVID-19 detection in Ethics and Explainability for Responsible Data Science (EE-RDS) conference 2021, we proposed a method which combined Swin Transformer and Transformer in Transformer to classify chest X-ray images as three classes: COVID-19, Pneumonia and Normal (healthy) and achieved 0.9475 accuracy on test set.
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