Accurate crop yield prediction is critical for global food security, economic planning, and insurance modeling. Traditional process-based (PB) models rely on biophysical equations and empirical data, ...

Crop Yield Prediction Using Federated Learning This is the official documentation of the code repository of the paper: Patrick Killeen, Iluju Kiringa, and Tet Yeap "UAV Imagery-Based Yield Prediction ...

Technology adoption can address these issues, improving production and quality. Machine learning, a subset of Artificial Intelligence (AI), enables prediction, classification, and automation in ...

The timely and accurate prediction of maize (Zea mays L.) yields prior to harvest is critical for food security and agricultural policy development. Currently, many researchers are using machine ...

A new machine-learning model for predicting crop yield using environmental data and genetic information can be used to develop new, higher-performing crop varieties.

The Crop Yield Prediction pattern leverages machine learning (ML) to forecast future agricultural crop yields. This pattern is critical in assisting farmers and agricultural planners in maximizing ...

By reanalyzing the prior crop growth model with multi-temporal observation data, the reliability of the simulation results is improved, which is of great significance to agricultural dynamic ...