Name
Abstract | ||
|---|---|---|
Autonomous Unmanned Aerial Vehicles (UAVs) provide an effective alternative for surveillance in urban areas due to their cost and safety when compared to other traditional methods. The objective of this study is to report the development of a system capable of analyzing digital images of the terrain and identifying potential invasion, unauthorized changes in land and deforestation in some special urban areas. Images are captured by a camera attached to an autonomous helicopter, flying it around the area. For processing the images, an Artificial Neural Network (ANN) technique called Self Organizing Map (SOM) is used. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/HIS.2013.6920414 | Hybrid Intelligent Systems |
Keywords | DocType | ISBN |
autonomous aerial vehicles,helicopters,neurocontrollers,robot vision,self-organising feature maps,surveillance,ANN,SOM,UAV,artificial neural network,autonomous helicopter,autonomous unmanned aerial vehicles,deforestation,digital image,land,self organizing map,terrain surveillance,urban area,Kohonen SOM,Pattern recognition,UAV,autonomous helicopter,surveillance | Conference | 978-1-4799-2438-7 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luiz F. Felizardo | 1 | 0 | 0.34 |
| Rodrigo L. Mota | 2 | 0 | 0.34 |
| Elcio H. Shiguemori | 3 | 1 | 0.72 |
| Marcos T. Neves | 4 | 0 | 0.34 |
| Alexandre C. B. Ramos | 5 | 1 | 0.82 |
| Félix Mora-Camino | 6 | 41 | 12.11 |