Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images
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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Düzce University
2022-04-01
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| Series: | Düzce Üniversitesi Bilim ve Teknoloji Dergisi |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/download/article-file/1898459 |
| _version_ | 1797300817504501760 |
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| author | Durmuş Özdemir Naciye Nur Arslan |
| author_facet | Durmuş Özdemir Naciye Nur Arslan |
| author_sort | Durmuş Özdemir |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-07T23:13:30Z |
| format | Article |
| id | doaj.art-fa5f2726458d40e698e9678a2754be3c |
| institution | Directory Open Access Journal |
| issn | 2148-2446 |
| language | English |
| last_indexed | 2024-03-07T23:13:30Z |
| publishDate | 2022-04-01 |
| publisher | Düzce University |
| record_format | Article |
| series | Düzce Üniversitesi Bilim ve Teknoloji Dergisi |
| spelling | doaj.art-fa5f2726458d40e698e9678a2754be3c2024-02-21T14:07:30ZengDüzce UniversityDüzce Üniversitesi Bilim ve Teknoloji Dergisi2148-24462022-04-0110262864010.29130/dubited.97611897Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray ImagesDurmuş Özdemir0Naciye Nur Arslan1KUTAHYA DUMLUPINAR UNIVERSITYKUTAHYA DUMLUPINAR UNIVERSITYThis 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.https://dergipark.org.tr/tr/download/article-file/1898459biyomedikal bilişimderin öğrenmecovid-19 teşhisigörüntü sınıflandırmabiomedical informaticsdeep learningcovid-19 diagnosisimage classification |
| spellingShingle | Durmuş Özdemir Naciye Nur Arslan Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images Düzce Üniversitesi Bilim ve Teknoloji Dergisi biyomedikal bilişim derin öğrenme covid-19 teşhisi görüntü sınıflandırma biomedical informatics deep learning covid-19 diagnosis image classification |
| title | Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images |
| title_full | Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images |
| title_fullStr | Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images |
| title_full_unstemmed | Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images |
| title_short | Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images |
| title_sort | analysis of deep transfer learning methods for early diagnosis of the covid 19 disease with chest x ray images |
| topic | biyomedikal bilişim derin öğrenme covid-19 teşhisi görüntü sınıflandırma biomedical informatics deep learning covid-19 diagnosis image classification |
| url | https://dergipark.org.tr/tr/download/article-file/1898459 |
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