Name
Abstract | ||
|---|---|---|
Cloud detection is one of the important tasks for remote sensing image processing. In this paper, a novel multilevel cloud detection method based on deep learning is proposed for remote sensing images. First, the simple linear iterative clustering (SLIC) method is improved to segment the image into good quality superpixels. Then, a deep convolutional neural network (CNN) with two branches is desig... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSTARS.2017.2686488 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Clouds,Remote sensing,Image color analysis,Feature extraction,Machine learning,Image segmentation,Clustering algorithms | Computer vision,Cloud detection,Convolutional neural network,Remote sensing,Image segmentation,Robustness (computer science),Feature extraction,Artificial intelligence,Deep learning,Cluster analysis,Mathematics,Cloud computing | Journal |
Volume | Issue | ISSN |
10 | 8 | 1939-1404 |
Citations | PageRank | References |
12 | 0.77 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fengying Xie | 1 | 182 | 15.33 |
| Mengyun Shi | 2 | 16 | 1.23 |
| Zhenwei Shi | 3 | 559 | 63.11 |
| Jihao Yin | 4 | 90 | 12.18 |
| Danpei Zhao | 5 | 75 | 9.07 |