Research output per year
Research output per year
Project Details
Description
The project explores way to apply machine learning and deep learning method for crop yield forecasting at scale (e.g. multiple crops and countries in Europe). Objective is to assess the benefits of machine learning in providing reliable and interpretable forecasts.
| Status | Finished |
|---|---|
| Effective start/end date | 1/03/19 → 13/06/23 |
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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A weakly supervised framework for high-resolution crop yield forecasts
Paudel, D., Marcos, D., de Wit, A., Boogaard, H. & Athanasiadis, I., 1 Sept 2023, In: Environmental Research Letters. 18, 9, 094062.Research output: Contribution to journal › Article › Academic › peer-review
Open Access2 Citations (Scopus) -
Machine learning for large-scale crop yield forecasting
Paudel, D., 13 Jun 2023, Wageningen: Wageningen University. 193 p.Research output: Thesis › internal PhD, WU
Open Access