Name
Abstract | ||
|---|---|---|
Recently, deep neural networks achieved state-of-the-art results on the automated diagnosis of skin lesions. Both the availability of bigger and better datasets as well as major advancements in Convolutional Neural Network methodologies represent some of the reasons behind these results. While the former is powered by initiatives like the International Skin Imaging Collaboration (ISIC), the latter... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/INISTA52262.2021.9548455 | 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA) |
Keywords | DocType | ISBN |
Training,Deep learning,Technological innovation,Computational modeling,Transfer learning,Computer architecture,Skin | Conference | 978-1-6654-3603-8 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fábio Santos | 1 | 1 | 0.69 |
| Filipe M. T. Silva | 2 | 65 | 14.07 |
| Petia Georgieva | 3 | 81 | 17.45 |