| 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 |