A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools
Purdue University West Lafayette
Abstract
Several factors associated with disease diagnosis in plants using deep learning techniques must be considered to develop a robust system for accurate disease management. A considerable number of studies have investigated the potential of deep learning techniques for precision agriculture in the last decade. However, despite the range of applications, several gaps within plant disease research are yet to be addressed to support disease management on farms. Thus, there is a need to establish a knowledge base of existing applications and identify the challenges and opportunities to help advance the development of tools that address farmers' needs. This study presents a comprehensive overview of 70 studies on deep…
Citation impact
- FWCI
- 63.20
- Percentile
- 100%
- References
- 150
Authors
3Topics & keywords
- Deep learning
- Artificial intelligence
- Computer science
- Machine learning
- Usability
- Data science
- Plant disease
- Precision agriculture
- Zero hunger