Bridging the gap between hyperspectral imaging and crop breeding: soybean yield prediction and lodging classification with prototype contrastive learning.

Accurately estimate soybean growth stages from UAV imagery by accounting for spatial heterogeneity and climate factors across multiple environments.

High-quality images and data augmentation based on inverse projection transformation significantly improve the estimation accuracy of biomass and leaf area index.

Estimation of sugar content in sugar beet root based on UAV multi-sensor data.

Detection of Maize Tassels from UAV RGB Imagery with Faster R-CNN.