Leveraging deep learning for plant disease and pest detection: a comprehensive review and future directions
CECOS University · Sejong University · +3 more institutions
Abstract
Plant diseases and pests pose significant threats to crop yield and quality, prompting the exploration of digital image processing techniques for their detection. Recent advancements in deep learning models have shown remarkable progress in this domain, outperforming traditional methods across various fronts including classification, detection, and segmentation networks. This review delves into recent research endeavors focused on leveraging deep learning for detecting plant and pest diseases, reflecting a burgeoning interest among researchers in artificial intelligence-driven approaches for agricultural analysis. The study begins by elucidating the limitations of conventional detection methods, setting the…
Citation impact
- FWCI
- 103.13
- Percentile
- 100%
- References
- 64
Authors
5Topics & keywords
- Deep learning
- Artificial intelligence
- Computer science
- Transformative learning
- Machine learning
- Data science
- Zero hunger