Name
Abstract | ||
|---|---|---|
Despite of the substantial success of Convolutional Neural Networks (CNNs) on many recognition and representation tasks, such models are very reliant on huge amount of data to allow effective training. In order to improve the generalization ability of CNNs, several approaches have been proposed, including variations of data augmentation strategies. With the goal of achieving more effective retriev... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SIBGRAPI54419.2021.00063 | 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) |
Keywords | DocType | ISSN |
Representation learning,Training,Manifolds,Solid modeling,Three-dimensional displays,Image retrieval,Transfer learning | Conference | 1530-1834 |
ISBN | Citations | PageRank |
978-1-6654-2354-0 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas Barbosa de Almeida | 1 | 0 | 0.34 |
| Vanessa Helena Pereira-Ferrero | 2 | 0 | 0.34 |
| Lucas Pascotti Valem | 3 | 7 | 5.80 |
| Jurandy Almeida | 4 | 0 | 0.34 |
| Daniel Carlos Guimarães Pedronette | 5 | 0 | 0.34 |