Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images
| dc.contributor.author | Özdemir, Durmuş | |
| dc.contributor.author | Bilici, Zehra | |
| dc.date.accessioned | 2023-04-10T20:29:32Z | |
| dc.date.available | 2023-04-10T20:29:32Z | |
| dc.date.issued | 2022 | |
| dc.department | Rektörlük, Rektörlüğe Bağlı Birimler, Düzce Üniversitesi Dergileri | en_US |
| dc.description.abstract | This study aimed to present an analysis of deep transfer learning models to support the early diagnosis of Covid- 19 disease using X-ray images. For this purpose, the deep transfer learning models VGG-16, VGG-19, Inception V3 and Xception, which were successful in the ImageNet competition, were used to detect Covid-19 disease. Also, 280 chest x-ray images were used for the training data, and 140 chest x-ray images were used for the test data. As a result of the statistical analysis, the most successful model was Inception V3 (%92), the next successful model was Xception (%91), and the VGG-16 and VGG-19 models gave the same result (%88). The proposed deep learning model offers significant advantages in diagnosing covid-19 disease issues such as test costs, test accuracy rate, staff workload, and waiting time for test results. | en_US |
| dc.identifier.doi | 10.29130/dubited.976118 | |
| dc.identifier.endpage | 640 | en_US |
| dc.identifier.issn | 2148-2446 | |
| dc.identifier.issue | 2 | en_US |
| dc.identifier.startpage | 628 | en_US |
| dc.identifier.trdizinid | 1124505 | en_US |
| dc.identifier.uri | http://doi.org/10.29130/dubited.976118 | |
| dc.identifier.uri | https://search.trdizin.gov.tr/yayin/detay/1124505 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12684/11911 | |
| dc.identifier.volume | 10 | en_US |
| dc.indekslendigikaynak | TR-Dizin | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartof | Düzce Üniversitesi Bilim ve Teknoloji Dergisi | |
| dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Biyomedikal bilişim | en_US |
| dc.subject | Derin öğrenme | en_US |
| dc.subject | Covid-19 teşhisi | en_US |
| dc.subject | Görüntü sınıflandırma | en_US |
| dc.title | Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images | en_US |
| dc.type | Article | en_US |
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