A densely interconnected convolutional neural network-based approach to identify COVID-19 from Chest X-ray Images
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...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Springer Science and Business Media Deutschland GmbH
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/39633/ 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 |
Internet
http://umpir.ump.edu.my/id/eprint/39633/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