2 papers
cs.AI2026
AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress
Yue Shi, Liangxiu Han, Xin Zhang +7
Accurate prediction of crop above-ground biomass (AGB) under water stress is critical for monitoring crop productivity, guiding irrigation, and supporting climate-resilient agricul…
cs.LG2025
Deep Learning Meets Process-Based Models: A Hybrid Approach to Agricultural Challenges
Yue Shi, Liangxiu Han, Xin Zhang +7
Process-based models (PBMs) and deep learning (DL) are two key approaches in agricultural modelling, each offering distinct advantages and limitations. PBMs provide mechanistic ins…