Name
Abstract | ||
|---|---|---|
A very large volume of images is uploaded to the Internet daily. However, current hashing methods for image retrieval are designed for static databases only. They fail to consider the fact that the distribution of images can change when new images are added to the database over time. The changes in the distribution of images include both discovery of a new class and a distribution of images within... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCYB.2016.2582530 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Semantics,Image retrieval,Internet,Cybernetics,Computer science,Computers | Data mining,Automatic image annotation,Ranking,Computer science,Upload,Image retrieval,Concept drift,Artificial intelligence,Hash function,Machine learning,Visual Word,Hash table | Journal |
Volume | Issue | ISSN |
47 | 11 | 2168-2267 |
Citations | PageRank | References |
6 | 0.45 | 28 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wing W. Y. Ng | 1 | 528 | 56.12 |
| Xing Tian | 2 | 16 | 3.27 |
| Yueming Lv | 3 | 16 | 0.92 |
| Daniel S. Yeung | 4 | 1126 | 92.97 |
| W. Pedrycz | 5 | 13966 | 1005.85 |