5 citations · 5 across the 2 of their papers we have counts for
4 papers
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…
A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management
Shen Tan, Xin Zhang, Liangxiu Han +2
Accurate, cost-effective monitoring of plantation aboveground biomass (AGB) is crucial for supporting local livelihoods and carbon sequestration initiatives like the China Certifie…
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…
TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration
Xin Zhang, Liangxiu Han, Stephen White +5
Acute Coronary Syndromes (ACS), including ST-segment elevation myocardial infarctions (STEMI) and non-ST-segment elevation myocardial infarctions (NSTEMI), remain a leading cause o…