Name
Title | ||
|---|---|---|
Automatic Water-Body Segmentation From High-Resolution Satellite Images via Deep Networks. |
Abstract | ||
|---|---|---|
Water-body segmentation is an important issue in remote sensing and image interpretation. Classic methods for counteracting this problem usually include the construction of index features by combining different spectra, however, these methods are essentially rule-based and fail to take advantage of context information. Additionally, as the quality of image resolution improves, these methods are pr... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LGRS.2018.2794545 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Convolution,Image segmentation,Remote sensing,Deconvolution,Kernel,Indexes,Image resolution | Kernel (linear algebra),Computer vision,Weighting,Segmentation,Convolutional neural network,Deconvolution,Image segmentation,Pixel,Artificial intelligence,Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
15 | 4 | 1545-598X |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ziming Miao | 1 | 1 | 0.34 |
| Kun Fu | 2 | 414 | 57.81 |
| Hao Sun | 3 | 140 | 11.86 |
| Xian Sun | 4 | 26 | 4.55 |
| Menglong Yan | 5 | 50 | 8.33 |