A systematic review of deep learning techniques for plant diseases
Iğdır Üniversitesi · VSB - Technical University of Ostrava · +5 more institutions
Abstract
Agriculture is one of the most crucial sectors, meeting the fundamental food needs of humanity. Plant diseases increase food economic and food security concerns for countries and disrupt their agricultural planning. Traditional methods for detecting plant diseases require a lot of labor and time. Consequently, many researchers and institutions strive to address these issues using advanced technological methods. Deep learning-based plant disease detection offers considerable progress and hope compared to classical methods. When trained with large and high-quality datasets, these technologies robustly detect diseases on plant leaves in early stages. This study systematically reviews the application of deep…
Citation impact
- FWCI
- 90.56
- Percentile
- 100%
- References
- 159
Authors
8Topics & keywords
- Computer science
- Artificial intelligence
- Deep learning
- Machine learning
- Zero hunger