dc.contributor.author |
Thavarasa, Deneshwaran |
|
dc.date.accessioned |
2022-12-16T09:25:16Z |
|
dc.date.available |
2022-12-16T09:25:16Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Thavarasa, Deneshwaran (2022) COVID-19 Pneumonia Cases Were Detected Automatically Using Deep Learning Model and X-Ray Images. BEng. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2017057 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1139 |
|
dc.description.abstract |
This (COVID-19) is spreading quickly around the globe. COVID-19 victims have been diagnosed and isolated early, which has helped to slow the virus's spread. Deep learning algorithms are one of the greatest solutions for accurately and quickly recognizing COVID-19. This paper proposes two distinct DL techniques for COVID-19 identification utilizing chest X- ray pictures, both using on a connected CNN model. This preprocessing stage involves augmentation, enhancement, normalization, and resizing CXR images to a defined size. This study presents a deep learning method for identifying CXR pictures based on an assembly of many iterations of a revised. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
convolutional neural network |
en_US |
dc.subject |
Chest X-ray |
en_US |
dc.subject |
Computed Tomography Scan |
en_US |
dc.title |
COVID-19 Pneumonia Cases Were Detected Automatically Using Deep Learning Model and X-Ray Images |
en_US |
dc.type |
Thesis |
en_US |