Papers

2

Total Citations

9

H-Index

2

About

Lijiao Wei is a rising leader in agricultural robotics and edge-AI, whose work is redefining how machines perceive and interact with complex natural environments. Her research centers on developing lightweight, high-precision deep learning models for real-time crop detection and localization, specifically optimized for resource-constrained edge devices. Wei’s major contribution is the creation of Slim-Banana, an efficient convolutional neural network that, for the first time, enables banana detection and 3D localization directly on edge hardware. By integrating a RealSense depth sensor with Time-of-Flight technology, her system achieves precise positioning in cluttered orchard settings, a critical step toward fully autonomous harvesting. Her subsequent work, EdgeSugarcane, tackles the equally challenging task of sugarcane node detection, overcoming the pitfalls of large, deployment-unfriendly models. Though early in her career, her papers have already garnered citations (e.g., 6 for her banana detection work), signaling strong impact. Wei’s achievements demonstrate a rare ability to bridge cutting-edge computer vision with practical, deployable solutions for precision agriculture, making her a researcher to watch in the field of intelligent farming systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
9
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
An efficient and lightweight banana detection and localization system based on deep CNNs for agricultural robots
6 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Chinese Academy of Tropical Agricultural Sciences

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago