Accuracy of a smartphone-based object detection model, PlantVillage Nuru, in identifying the foliar symptoms of the viral diseases of cassava-CMD and CBSD
Nuru is a deep learning object detection model for diagnosing plant diseases and pests developed as a public good by PlantVillage (Penn State University), FAO, IITA, CIMMYT, and others. It provides a simple, inexpensive and robust means of conducting in-field diagnosis without requiring an internet...
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Frontiers Media
2020
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/119277 |
Ejemplares similares: Accuracy of a smartphone-based object detection model, PlantVillage Nuru, in identifying the foliar symptoms of the viral diseases of cassava-CMD and CBSD
- A mobile-based deep learning model for cassava disease diagnosis
- Scaling of digital extension tools (PlantVillage NURU app) for diagnosis of cassava pests and diseases
- CBSD
- AMPPPIDA Results from Tanzania
- Exchanging and managing in-vitro elite germplasm to combat cassava brown streak disease (CBSD) and cassava mosaic disease (CMD) in Eastern and Southern Africa
- A survey of cassava plants in the coastal region of Tanzania showing severe symptoms of cassava mosaic disease