Name
Title | ||
|---|---|---|
Mapping of Rumex obtusifolius in nature conservation areas using very high resolution UAV imagery and deep learning |
Abstract | ||
|---|---|---|
•Seven CNN models were applied to evaluate their feasibility on detecting Rumex.•Three flight heights were tested to choose the best configuration for Rumex mapping.•The minimum spatial resolution required for Rumex detection was provided.•The datasets and code used in this research are available to the scientific community in public repository. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.jag.2022.102864 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | DocType | Volume |
UAV,Deep learning,Transfer learning,Weed detection,Rumex | Journal | 112 |
ISSN | Citations | PageRank |
1569-8432 | 0 | 0.34 |
References | Authors | |
5 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joao Valente | 1 | 0 | 0.34 |
| Santosh Hiremath | 2 | 0 | 0.34 |
| Mar Ariza-Sentis | 3 | 0 | 0.34 |
| Marty Doldersum | 4 | 0 | 0.34 |
| Lammert Kooistra | 5 | 0 | 0.34 |