Name
Abstract | ||
|---|---|---|
•A comprehensive study that explores deep convolutional features for CBIR.•The paper evaluates recently proposed CNNs architectures in image retrieval tasks.•A plug-n-play approach that uses new architectures of pre-trained CNN’s for CBIR.•The performance of each network is evaluated using global and local descriptors. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.114940 | Expert Systems with Applications |
Keywords | DocType | Volume |
Image retrieval,Deep convolutional features,Deep learning,CNN,Global features,Local features,CBIR | Journal | 177 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Socratis Gkelios | 1 | 0 | 0.34 |
| Aphrodite Sophokleous | 2 | 0 | 0.34 |
| Spyridon Plakias | 3 | 0 | 2.03 |
| Yiannis Boutalis | 4 | 531 | 26.85 |
| Savvas A. Chatzichristofis | 5 | 810 | 44.88 |