CP23351Detection and severity assessment of tea leaf blight from UAV remote sensing images
Protecting tea plants from devastating diseases is crucial for maintaining yield and quality. This study utilized ECDet and MobileNetv3 networks to detect and assess the severity of tea leaf blight by using remote sensing images captured by an unmanned aerial vehicle. The proposed method achieved an impressive detection precision and high accuracy in assessing leaf damage severity, offering a promising and efficient solution with broader implications for improved disease management in tea production.