Rift Valley fever (RVF) project on Zooniverse, a citizen science platform that allows registered volunteers to identify animals in landscapes from drone imagery
A4NH researchers from the London School of Hygiene and Tropical Medicine set up this project page on Zooniverse, pending beta review and a public launch. In addition to its role in developing transmission models, the data could be used for developing machine learning algorithms to automatically iden...
| Autor principal: | |
|---|---|
| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2021
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/122825 |
Ejemplares similares: Rift Valley fever (RVF) project on Zooniverse, a citizen science platform that allows registered volunteers to identify animals in landscapes from drone imagery
- Boosting Uganda's investment in Livestock Development: RVF component
- Machine learning approach to predicting Rift Valley fever disease outbreaks in Kenya
- An XGBoost approach to predictive modelling of Rift Valley fever outbreaks in Kenya using climatic factors
- A systematic literature review with meta-analysis of predictive modelling of Rift Valley fever outbreaks in East Africa: Machine learning and time series approaches
- Detection of Rift Valley fever virus interepidemic activity in some hotspot areas of Kenya by sentinel animal surveillance, 2009–2012
- Rift Valley Fever and the Changing Environment