Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review
Chinese Academy of Sciences · Institute of Remote Sensing and Digital Earth · +3 more institutions
Abstract
Traditional methods for detecting plant diseases and pests are time-consuming, labor-intensive, and require specialized skills and resources, making them insufficient to meet the demands of modern agricultural development. To address these challenges, deep learning technologies have emerged as a promising solution for the accurate and timely identification of plant diseases and pests, thereby reducing crop losses and optimizing agricultural resource allocation. By leveraging its advantages in image processing, deep learning technology has significantly enhanced the accuracy of plant disease and pest detection and identification. This review provides a comprehensive overview of recent advancements in applying…
Citation impact
- FWCI
- 179.60
- Percentile
- 100%
- References
- 184
Authors
8- SWShaohua WangCorresponding
Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Aerospace Information Research Institute
- DXDachuan Xu
Chinese Academy of Sciences, Lanzhou Jiaotong University, Institute of Remote Sensing and Digital Earth, Aerospace Information Research Institute
- HLHaojian Liang
Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Aerospace Information Research Institute
- YBYongqing Bai
Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Aerospace Information Research Institute
- XLXiao Li
Chinese Academy of Sciences, Lanzhou Jiaotong University, Institute of Remote Sensing and Digital Earth, Aerospace Information Research Institute
Topics & keywords
- Plant disease
- Biology
- Biotechnology