A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: An Experimental Case on a Limited COVID-19 Chest X-Ray Dataset

Download or read book A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: An Experimental Case on a Limited COVID-19 Chest X-Ray Dataset written by Nour Eldeen M. Khalifa and published by Infinite Study. This book was released on with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: Coronavirus, also known as COVID-19, has spread to several countries around the world. It was announced as a pandemic disease by The World Health Organization (WHO) in 2020 for its devastating impact on humans. With the advancements in computer science algorithms, the detection of this type of virus in the early stages is urgently needed for the fast recovery of patients. In this paper, a study of neutrosophic set significance on deep transfer learning models over a limited COVID-19 chest x-ray dataset will be presented. The study relies on neutrosophic set theory, as it shows a huge potential for solving many computers problems related to the detection, and the classification domains.