Crop yield predictions using sequential UAV imagery and deep learning
This study investigates the use of sequential UAV (Unmanned Airborne Vehicle) imagery and deep learning for crop yield predictions. Accurate crop yield predictions are crucial for mitigating food shortages and making informed agricultural decisions. This research uses different sequence lengths of UAV images across five wavelength bands to model winter wheat, spring wheat, and barley crop yield in