Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques

Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms, sensors and software, UAVs have gained popularity among precision agriculture researchers stakeholders for estimating traits such as crop yield diseases. Early detection disease is essential to prevent possible losses on ultimately increasing benefits. However, accurate estimation requires modern data analysis techniques machine learning deep learning. This work aims review actual progress detection, with an emphasis using UAV-based remote sensing. First, we present importance different image-processing improving UAV imagery. Second, propose a taxonomy accumulate categorize existing works Third, analyze summarize performance various methods detection. Finally, underscore challenges, opportunities research directions sensing