Name
Title | ||
|---|---|---|
Airport Detection on Optical Satellite Images Using Deep Convolutional Neural Networks. |
Abstract | ||
|---|---|---|
This letter proposes a method using convolutional neural networks (CNNs) for airport detection on optical satellite images. To efficiently build a deep CNN with limited satellite image samples, a transfer learning approach had been employed by sharing the common image features of the natural images. To decrease the computing cost, an efficient region proposal method had been proposed based on the ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LGRS.2017.2673118 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Airports,Proposals,Satellites,Joining processes,Optical imaging,Feature extraction,Image segmentation | Computer vision,Line segment,Satellite,Feature (computer vision),Convolutional neural network,Remote sensing,Transfer of learning,Feature extraction,Image segmentation,Artificial intelligence,Mathematics,Computation | Journal |
Volume | Issue | ISSN |
14 | 8 | 1545-598X |
Citations | PageRank | References |
6 | 0.45 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Zhang | 1 | 48 | 5.09 |
| Xin Niu | 2 | 56 | 11.39 |
| Yong Dou | 3 | 632 | 89.67 |
| Fei Xia | 4 | 6 | 0.45 |