Abstract :

COVID-19 has created havoc in the world. This paper aims to study and understand the performance of modified VGG-16 and VGG-19 architectures in detecting COVID-19 using the concept of transfer learning. The algorithm has been validated using a private dataset with normal and COVID-19 positive chest X-ray images.

COVID-19 has created havoc in the world. This paper aims to study and understand the performance of modified VGG-16 and VGG-19 architectures in detecting COVID-19 using the concept of transfer learning. The algorithm has been validated using a private dataset with normal and COVID-19 positive chest X-ray images.

---

Keywords :

CNN, COVID-19, Deep learning, Transfer learning, X-ray.

---

References :

1. Thakur, Y. Goplani, S. Arora, R. Upadhyay, G. Sharma, “Chest X-Ray Images Based Automated Detection of Pneumonia Using Transfer Learning and CNN,” Proceedings of International Conference on Artificial Intelligence and Applications Advances in Intelligent Systems and Computing, Vol. 1164, Springer, Singapore, 2021.
2. Salehi, R. Mohammadi, H. Ghaffari, N. Sadighi, and R. Reiazi, “Automated Detection of Pneumonia Cases Using Deep Transfer Learning with Pediatric Chest X-ray Images,” The British Journal of Radiology, Vol. 94, No. 1121, 2021.
3. Brima, M. Atemkeng, S.T. Djiokap, J. Ebiele, F. Tchakounté, “Transfer Learning for the Detection and Diagnosis of Types of Pneumonia including Pneumonia Induced by COVID-19 from Chest X-ray Images,” Journal of Diagnostics, Vol. 11, 2021.
4. Srivastav, A. Bajpai, P. Srivastava, “Improved Classification for Pneumonia Detection using Transfer Learning with GAN based Synthetic Image Augmentation,” 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2021.
5. Chakraborty, S. Paul, K.M.A. Hasan, “A Transfer Learning-Based Approach with Deep CNN for COVID-19 and Pneumonia-Affected Chest X-ray Image Classification,” S.N. Computer Science, 2021.