Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques
Central Queensland University · Charles Darwin University
Abstract
Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms, sensors and software, UAVs have gained popularity among precision agriculture researchers and stakeholders for estimating traits such as crop yield and diseases. Early detection of crop disease is essential to prevent possible losses on crop yield and ultimately increasing the benefits. However, accurate estimation of crop disease requires modern data analysis techniques such as machine learning and deep learning. This work aims to review the actual progress in crop disease detection, with an emphasis on machine learning and deep learning techniques using UAV-based remote sensing. First, we present the importance of different…
Citation impact
- FWCI
- 92.21
- Percentile
- 100%
- References
- 131
Authors
4Topics & keywords
- Drone
- Computer science
- Deep learning
- Artificial intelligence
- Machine learning
- Categorization
- Precision agriculture
- Crop
- Zero hunger