COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader
| dc.contributor.author | Abeer Sawalha | |
| dc.date.accessioned | 2023-05-16T11:47:25Z | |
| dc.date.available | 2023-05-16T11:47:25Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Chest X-ray imaging has been proved as a powerful diagnostic method to detect and diagnose COVID-19 cases due to its easy accessibility, lower cost and rapid imaging time. Objective This study aims to improve efficacy of screening COVID-19 infected patients using chest X ray images with the help of a developed deep convolutional neural network model (CNN) entitled nCoV-NET. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11888/18265 | |
| dc.supervisor | Dr. Allam Mousa | |
| dc.title | COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader |
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