Name
Abstract | ||
|---|---|---|
For image retrieval methods based on bag of visual words, much attention has been paid to enhancing the discriminative powers of the local features. Although retrieved images are usually similar to a query in minutiae, they may be significantly different from a semantic perspective, which can be effectively distinguished by convolutional neural networks (CNN). Such images should not be considered ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2845136 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Kernel,Image retrieval,Semantics,Visualization,Feature extraction,Indexing | Kernel (linear algebra),Bag-of-words model in computer vision,Pattern recognition,Minutiae,Convolutional neural network,Search engine indexing,Image retrieval,Feature extraction,Artificial intelligence,Discriminative model,Mathematics | Journal |
Volume | Issue | ISSN |
27 | 11 | 1057-7149 |
Citations | PageRank | References |
5 | 0.39 | 37 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jufeng Yang | 1 | 61 | 9.97 |
| jie liang | 2 | 26 | 10.90 |
| Hui Shen | 3 | 134 | 15.32 |
| Kai Wang | 4 | 1734 | 195.03 |
| Paul L. Rosin | 5 | 2559 | 254.25 |
| Yang Ming-Hsuan | 6 | 15303 | 620.69 |