Said Thaufik Rizaldi, Said Penerapan Image Enhancement pada Deep Learning untuk Identifikasi Paru-Paru COVID-19. The 2022 International Symponsium on Information Technology and Digital Innovations. (In Press)
|
Text
Said Thaufik Rizaldi_11753101376.pdf Download (4MB) | Preview |
Abstract
The Novel Coronavirus Disease 2019 (COVID-19) is continuously a phenomenon that continues to study for its development throughout the world because of its international emergency status. The act of testing by clinical laboratory experts is a preventive effort to reduce the increase in cases. However, the number of experts is minimal compared to the cases. So with deep learning, we need the best model for classifying lung disease variants that the world of health can utilize. This study applies several image enhancement techniques to the convolutional neural network algorithm ResNet50 architecture, which produces gamma correction as the best image improvement technique in this study with an accuracy of 0.986. These techniques also have a reasonably efficient time and a good loss value.
| Item Type: | Article |
|---|---|
| Subjects: | 600 Teknologi dan Ilmu-ilmu Terapan |
| Divisions: | Fakultas Sains dan Teknologi > Sistem Informasi |
| Depositing User: | fsains - |
| Date Deposited: | 22 Jul 2022 04:02 |
| Last Modified: | 22 Jul 2022 04:02 |
| URI: | http://repository.uin-suska.ac.id/id/eprint/61748 |
Actions (login required)
 |
View Item |