Name
Title | ||
|---|---|---|
LIME-Enabled Investigation of Convolutional Neural Network Performances in COVID-19 Chest X-Ray Detection |
Abstract | ||
|---|---|---|
The Coronavirus Disease (COVID-19) has caused millions of casualties across the globe. One inexpensive and noninvasive screening method for COVID-19 is the analysis of chest X-ray (CXR) images for pathological features in the lungs. These features are difficult to detect by humans, but convolutional neural networks (CNN) have proven effective at extracting them. This paper uses four ImageNet-pre-t... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CCECE53047.2021.9569029 | 2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) |
Keywords | DocType | ISSN |
COVID-19,Pulmonary diseases,Transfer learning,Lung,Predictive models,Feature extraction,Convolutional neural networks | Conference | 0840-7789 |
ISBN | Citations | PageRank |
978-1-6654-4864-2 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduardo Gasca Cervantes | 1 | 0 | 0.34 |
| W.-Y. Chan | 2 | 114 | 18.25 |