Yunshuang Wang
Papers
1
Total Citations
5
H-Index
1
About
Dr. Yunshuang Wang is a rising researcher in agricultural artificial intelligence, with a primary focus on precision weed detection and smart farming technologies. Her most-cited work introduces PHRF-RTDETR, a lightweight deep learning model based on RT-DETR that addresses the critical challenge of accurate weed identification in upland rice systems. This contribution is particularly significant because weeds in upland environments pose a greater threat to crop yield and quality than in paddy fields, yet existing detection methods often fall short in balancing accuracy and computational efficiency. By developing a model that is both effective and lightweight, Dr. Wang’s research enables real-time, deployable weed detection for intelligent weed control technologies—a key step toward sustainable, automated agriculture. With her work already garnering early citations, Dr. Wang is establishing herself as an innovator at the intersection of computer vision and agronomy, offering practical solutions that directly impact food security and farming efficiency.
Research Focus
Key Achievements
Top Papers
- 1