Papers
2
Total Citations
47
H-Index
2
About
Xiu Jin is a leading researcher in agricultural robotics and intelligent perception, whose work bridges the gap between precision agriculture and advanced artificial intelligence. Her key research areas include multimodal sensor fusion, deep learning for agricultural object detection, and efficient path planning for autonomous mobile robots. In her most-cited work, "MLP-based multimodal tomato detection in complex scenarios," she provides critical insights into feature fusion architectures, achieving 31 citations and advancing the reliability of vision systems in challenging field conditions. Her earlier foundational paper, "A Quadratic Traversal Algorithm of Shortest Weeding Path Planning for Agricultural Mobile Robots in Cornfield" (16 citations), introduced a time-efficient algorithm that dramatically improves weeding efficiency while protecting crops—a breakthrough for autonomous weed removal guidance. Together, these contributions demonstrate Jin’s ability to solve real-world agricultural challenges through innovative computational methods. Her work not only enhances the autonomy and precision of agricultural robots but also offers scalable solutions for sustainable farming. With a growing citation record and a focus on practical, task-specific AI, Xiu Jin is a rising voice in the field of smart agriculture and robotic perception.
Research Focus
Key Achievements
Top Papers
- 1
- 2