The coronavirus pandemic raised several challenges globally due to heavy demand for patient care and led researchers to find various methods to detect coronavirus. This work aims to provide a transfer learning (TL) based approach for detecting the COVID-19 cases by employing cloud computing thereby minimizing the processing time and costs. In contrast to the previous studies, we have used real-time COVID-19 positive cases chest X-ray images for the training of adopted pre-trained models such as VGG16, InceptionV3, and DenseNet121. The obtained results showed that VGG16 outperforms those models by 98.21% to precisely classify the COVID-19 positive and negative cases.
Vyas, Piyush; Ragothaman, Kaushik; Chauhan, Akhilesh; and Rimal, Bhaskar, "Classification of COVID-19 Cases: An Exploratory Study by Incorporating Transfer Learning with Cloud" (2021). MWAIS 2021 Proceedings. 8.