Name
Abstract | ||
|---|---|---|
Nowadays, unmanned aerial vehicles (UAVs) are viewed as effective acquisition platforms for several civilian applications. They can acquire images with an extremely high level of spatial detail compared to standard remote sensing platforms. However, these images are highly affected by illumination, rotation, and scale changes, which further increases the complexity of analysis compared to those ob... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TGRS.2018.2790926 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Support vector machines,Training,Feature extraction,Standards,Object detection,Remote sensing,Spatial resolution | Object detection,Computer vision,Data set,Convolutional neural network,Support vector machine,Feature extraction,Supervised learning,Artificial intelligence,Backpropagation,Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
56 | 6 | 0196-2892 |
Citations | PageRank | References |
7 | 0.58 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yakoub Bazi | 1 | 672 | 43.66 |
| Farid Melgani | 2 | 1100 | 80.98 |