Machine learning applied to high-throughput feature extraction from imagery to map spatial variability

This project will advance upon existing techniques for image analytics by setting up datasets from a greater range of situations, including different crops, locations, and image backgrounds. The information provided by this model can assist growers in making replant decisions, while improving yield estimation and increasing the ability to perform crop monitoring.