The employment of transfer learning for Covid-19 diagnostics: A ResNet evaluation

• Main Authors: Amiir Haamzah, Mohamed Ismail, Anwar, P. P. Abdul Majeed, E. H., Yap, A. H. P., Tan, Mohd Azraai, Mohd Razman, Ismail, Mohd Khairuddin, M. A., Abdullah
• Format: Conference or Workshop Item
• Language: English
• Published: 2022
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery; TK Electrical engineering. Electronics Nuclear engineering; TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/36979/1/The%20employment%20of%20transfer%20learning%20for%20covid-19%20diagnostics%20_%20A%20resnet%20evaluation.pdf; http://umpir.ump.edu.my/id/eprint/36979/; https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files

Artificial intelligence (AI) have made significant gains and contribution, particularly owing to the introduction of powerful graphical processing units in recent times. Furthermore, the advent of transfer learning models, which is a subset of deep learning models such as VGG16, InceptionV3, and Res...