A framework for predicting soft-fruit yields and phenology using embedded, networked microsensors, coupled weather models and machine-learning techniques. - Mark A. Lee; Angelo Monteiro; Andrew Barclay; Jon Marcar; Mirena Miteva-Neagu; Joe Parker (Comput. Electron. Agric., 2020)

The channel-spatial attention-based vision transformer network for automated, accurate prediction of crop nitrogen status from UAV imagery. - Xin Zhang 033; Liangxiu Han; Tam Sobeih; Lewis Lappin; Mark A. Lee; Andew Howard; Aron Kisdi (CoRR, 2021)

The Self-Supervised Spectral-Spatial Vision Transformer Network for Accurate Prediction of Wheat Nitrogen Status from UAV Imagery. - Xin Zhang 033; Liangxiu Han; Tam Sobeih; Lewis Lappin; Mark A. Lee; Andew Howard; Aron Kisdi (Remote. Sens., 2022)