Geographic-scale coffee cherry counting with smartphones and deep learning
Deep learning and computer vision, using remote sensing and drones, are 2 promising nondestructive methods for plant monitoring and phenotyping. However, their applications are infeasible for many crop systems under tree canopies, such as coffee crops, making it challenging...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2024
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/141476 |
Ejemplares similares: Geographic-scale coffee cherry counting with smartphones and deep learning
- Factors affecting deep learning model performance in citizen science–based image data collection for agriculture: A case study on coffee crops
- Effect of methods of processing on raw and intrinsic quality of Sidama and YirgaCheffee coffee types
- Rendimiento en la producción acuapónica de cinco variedades de tomate cherry, con carpa
- Ensayo de 4 variedades de tomate (2 variedades cherry y 2 variedades tomate redondo), Municipio de La Puerta, Dpto. Ambato
- Use of brillant blue dye on canned cherries
- Geographic indications and landscape labeling in Kodagu district, India