Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin
Front-line remote sensing tools, coupled with machine learning (ML), have a significant role in crop monitoring and disease surveillance. Crop type classification and a disease early warning system are some of these remote sensing applications that provide precise, timely, and cost-effective informa...
| Autores principales: | , , , , , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2020
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/110670 |
Ejemplares similares: Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin
- Validation of AI tools for disease recognition at large scale, available via a digital platform to support surveillance and breeding for resistance
- Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities
- Potenciando la investigación agrícola con modelos de inteligencia artificial
- Definición de parámetros en la toma de imágenes digitales para desarrollar métodos inteligentes de detección de enfermedades en vid
- Croppie: AI-powered information extraction from natural language
- AI-powered banana diseases and pest detection