Search Results for author:
Found 4 papers, 1 papers with code
Integrating processed-based models and machine learning for crop yield prediction
When tested on real-world data from field trials (n=303) and commercial fields (n=77), the meta-modeling approach yields competitive results with respect to the crop growth model.
Learning latent representations for operational nitrogen response rate prediction
We compare a Multilayer Perceptron, an Autoencoder, and a dual-head Autoencoder with a reference Random Forest model for nitrogen response rate prediction.
A weakly supervised framework for high-resolution crop yield forecasts
We propose a deep learning framework that uses high resolution inputs and low resolution labels to produce crop yield forecasts for both spatial levels.
CropGym: a Reinforcement Learning Environment for Crop Management
Nitrogen fertilizers have a detrimental effect on the environment, which can be reduced by optimizing fertilizer management strategies.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
