Xuan Ma
Papers
1
Total Citations
56
H-Index
1
About
Xuan Ma is a leading figure in agricultural artificial intelligence, with a primary focus on computer vision and deep learning for precision horticulture. Ma’s most influential work centers on developing lightweight, real-time object detection algorithms tailored for fruit ripeness assessment, directly addressing the critical need for efficient, automated harvesting in modern agriculture. Their landmark 2024 paper, “Lightweight tomato ripeness detection algorithm based on the improved RT-DETR,” has already garnered 56 citations, demonstrating immediate and substantial impact in the field. This research pioneers a novel approach that balances detection accuracy with computational efficiency, enabling deployment on resource-constrained devices for in-field applications. By refining the RT-DETR architecture, Ma has significantly advanced the selective harvesting of mature tomatoes, a crop of immense nutritional and economic value. This work not only enhances harvesting management efficiency but also reduces labor dependency and post-harvest losses. Ma’s contributions are pivotal in bridging the gap between cutting-edge AI and practical agricultural robotics, setting a new standard for intelligent, non-destructive fruit maturity classification that promises to reshape sustainable farming practices.
Research Focus
Key Achievements
Top Papers
- 1