COVID-19 Classification based on Neutrosophic Set Transfer Learning Approach

The COVID-19 virus has a significant impact on individuals around the globe. early diagnosis of this infectious disease is critical to preventing its global and local spread. In general, scientists have tested numerous ways methods detect people analyze virus. Interestingly, one used for X-rays that recognize whether person infected or not. Furthermore, researchers attempted use deep learning approaches yielded quicker more accurate results. This paper ResNet-50 module based Neutrosophic (NS) domain diagnose COVID patients over balanced database collected from radiography database. method future work N. E. M. Khalifa et al.’s NS set significance transfer learning. True (T), False (F), Indeterminate (I) membership sets were define chest X-ray images in domain. Experimental results confirmed proposed approach achieved 98.05% accuracy rate outperforming value acquired previously conducted studies within same