50 citations · 93 across the 10 of their papers we have counts for
10 papers
Flexible metadata harvesting for ecology using large language models
Zehao Lu, Thijs L van der Plas, Parinaz Rashidi +2
Large, open datasets can accelerate ecological research, particularly by enabling researchers to develop new insights by reusing datasets from multiple sources. However, to find th…
Integrating processed-based models and machine learning for crop yield prediction
Michiel G. J. Kallenberg, Bernardo Maestrini, Ron van Bree +4
Crop yield prediction typically involves the utilization of either theory-driven process-based crop growth models, which have proven to be difficult to calibrate for local conditio…
Evaluating Digital Agriculture Recommendations with Causal Inference
Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5
In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of smart farming tools. While AI-driven digital agriculture tools can offer hig…
Evaluating Digital Tools for Sustainable Agriculture using Causal Inference
Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5
In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of climate-smart farming tools. Even though AI-driven digital agriculture can o…
Learning latent representations for operational nitrogen response rate prediction
Christos Pylianidis, Ioannis N. Athanasiadis
Learning latent representations has aided operational decision-making in several disciplines. Its advantages include uncovering hidden interactions in data and automating procedure…
A weakly supervised framework for high-resolution crop yield forecasts
Dilli R. Paudel, Diego Marcos, Allard de Wit +2
Predictor inputs and label data for crop yield forecasting are not always available at the same spatial resolution. We propose a deep learning framework that uses high resolution i…