Name
Abstract | ||
|---|---|---|
Low cost remote sensing imagery has the potential to make precision farming feasible in developing countries. In this article, the authors describe image acquisition from eucalyptus, bean, and sugarcane crops acquired by low-cost and low-altitude systems. They use different approaches to handle low-altitude images in both the RGB and NIR (near-infrared) bands to estimate and quantify plantation ar... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/MCG.2016.69 | IEEE Computer Graphics and Applications |
Keywords | Field | DocType |
Remote sensing,Agriculture,Image recognition,Low altitude imaging,Vegatation mapping | Computer vision,Computer science,Remote sensing,Altitude,Precision agriculture,Artificial intelligence,RGB color model,Computer graphics | Journal |
Volume | Issue | ISSN |
36 | 4 | 0272-1716 |
Citations | PageRank | References |
3 | 0.43 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Moacir P. Ponti, Jr. | 1 | 32 | 3.60 |
| Arthur A. Chaves | 2 | 4 | 0.80 |
| Fábio R. Jorge | 3 | 3 | 0.43 |
| Gabriel B. P. Costa | 4 | 13 | 3.16 |
| Adimara Bentivoglio Colturato | 5 | 3 | 0.77 |
| Kalinka Regina Lucas Jaquie Castelo Branco | 6 | 45 | 8.40 |