Multi-Modal Machine Learning Framework for Accurate Crop Yield Prediction Using Soil, Weather, and Agricultural Data
Accurate predicting of crop yield is of greatest importance to the methods of precision agriculture and planning of food security. This study suggests a novel Multi-Modal Attention-Based Hybrid Deep Network (MAHDN) by combining heterogeneous data of agriculture, such as soil properties, weather parameters, and cropmana...