Name
Title | ||
|---|---|---|
Remote Sensing Image Retrieval Using Convolutional Neural Network Features and Weighted Distance. |
Abstract | ||
|---|---|---|
Remote sensing image retrieval (RSIR) is a fundamental task in remote sensing. Most content-based RSIR approaches take a simple distance as similarity criteria. A retrieval method based on weighted distance and basic features of convolutional neural network (CNN) is proposed in this letter. The method contains two stages. First, in offline stage, the pretrained CNN is fine-tuned by some labeled im... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LGRS.2018.2847303 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Remote sensing,Image retrieval,Feature extraction,Mathematical model,Computational modeling,Data models,Training | Data modeling,Computer vision,Weighted distance,Data set,Convolutional neural network,Remote sensing,Image retrieval,Feature extraction,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
15 | 10 | 1545-598X |
Citations | PageRank | References |
3 | 0.37 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Famao Ye | 1 | 10 | 1.14 |
| Hui Xiao | 2 | 29 | 6.96 |
| Xuqing Zhao | 3 | 8 | 0.77 |
| Meng Dong | 4 | 6 | 1.45 |
| Wei Luo | 5 | 5 | 0.76 |
| Weidong Min | 6 | 40 | 9.44 |