A densely interconnected convolutional neural network-based approach to identify COVID-19 from Chest X-ray Images

• المؤلفون الرئيسيون: Alfaz, Nazia, Sarwar, Talha, Das, Argho, Noorhuzaimi, Mohd Noor
• التنسيق: Conference or Workshop Item
• اللغة: English; English
• منشور في: Springer Science and Business Media Deutschland GmbH 2022
• الموضوعات: Q Science (General); QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• الوصول للمادة أونلاين: http://umpir.ump.edu.my/id/eprint/39633/1/A%20Densely%20Interconnected%20Convolutional%20Neural%20Network-Based%20Approach.pdf; http://umpir.ump.edu.my/id/eprint/39633/2/A%20densely%20interconnected%20convolutional%20neural%20network-based%20approach%20to%20identify%20COVID-19%20from%20Chest%20X-ray%20Images_ABS.pdf; http://umpir.ump.edu.my/id/eprint/39633/; https://doi.org/10.1007/978-981-16-8129-5_65

The novel Corona Virus (COVID-19) has spread so rapidly that cause a devastating effect on public well-being and create an emergency around the world. Hence, the rapid identification of COVID-19 has become a challenging work within a short period. Clinical trials of patients with COVID-19 have shown...