Name
Title | ||
|---|---|---|
EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing. |
Abstract | ||
|---|---|---|
Data acquired from multichannel sensors are a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sensors, and the constituent materials of a scene can be mixed in different fractions due to their spatial interactions. Spectral unmixing is a technique that allows us to obtain the mate... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TGRS.2018.2856929 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Hyperspectral imaging,Neural networks,Standards,Decoding,Microscopy,Spatial resolution | Journal | 57 |
Issue | ISSN | Citations |
1 | 0196-2892 | 4 |
PageRank | References | Authors |
0.39 | 43 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Savas Ozkan | 1 | 39 | 9.48 |
| Berk Kaya | 2 | 4 | 1.07 |
| Ersin Esen | 3 | 92 | 14.15 |
| Gozde Bozdagi Akar | 4 | 129 | 20.15 |