Name
Abstract | ||
|---|---|---|
In this letter, we propose a novel three-layer convex network termed as 3CN for domain adaptation in multitemporal very high resolution (VHR) remote sensing images. 3CN is composed of three main layers: 1) mapping source training samples to the target domain via a special single-layer feedforward neural network called extreme learning machine (ELM); 2) target image classification via ELM too; and ... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/LGRS.2015.2512999 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Training,Feature extraction,Kernel,Transforms,Yttrium,Sparse matrices,Image resolution | Kernel (linear algebra),Computer vision,Feedforward neural network,Pattern recognition,Feature detection (computer vision),Extreme learning machine,Network layer,Feature extraction,Artificial intelligence,Contextual image classification,Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
13 | 3 | 1545-598X |
Citations | PageRank | References |
2 | 0.36 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Essam Othman | 1 | 7 | 1.43 |
| Yakoub Bazi | 2 | 672 | 43.66 |
| Naif Alajlan | 3 | 839 | 50.51 |
| Haikel Al-Hichri | 4 | 31 | 4.09 |
| Farid Melgani | 5 | 1100 | 80.98 |