2 papers
cs.LG2022
In-Season Crop Progress in Unsurveyed Regions using Networks Trained on Synthetic Data
George Worrall, Jasmeet Judge
Many commodity crops have growth stages during which they are particularly vulnerable to stress-induced yield loss. In-season crop progress information is useful for quantifying cr…
cs.LG2021
Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation
George Worrall, Anand Rangarajan, Jasmeet Judge
Advanced machine learning techniques have been used in remote sensing (RS) applications such as crop mapping and yield prediction, but remain under-utilized for tracking crop progr…