Name
Abstract | ||
|---|---|---|
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. Deep learning techniques can generally provide state-of-the-art performance in many classification tasks when trained properly over large data sets. However, data scarcity can be... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TNNLS.2021.3070467 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
COVID-19,X-ray imaging,Diseases,Dictionaries,Training,Image recognition,Lung | Journal | 32 |
Issue | ISSN | Citations |
5 | 2162-237X | 0 |
PageRank | References | Authors |
0.34 | 9 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mehmet Yamac | 1 | 10 | 3.86 |
| Mete Ahishali | 2 | 2 | 1.04 |
| Aysen Degerli | 3 | 1 | 0.70 |
| Serkan Kiranyaz | 4 | 750 | 61.15 |
| Muhammad Chowdhury | 5 | 44 | 14.54 |
| Moncef Gabbouj | 6 | 3282 | 386.30 |