Runtian He

Northwest A&F University

Papers

1

Total Citations

78

H-Index

1

About

Runtian He is a researcher at the forefront of precision agriculture and computer vision, specializing in the development of efficient, real-time object detection systems for agricultural applications. His most significant contribution is the creation of a lightweight, channel-pruned YOLOv5s model for tracking and counting grape clusters in field conditions, a breakthrough that addresses the critical need for high-speed, low-resource AI in agricultural robotics. This work, published in 2023 and already garnering 78 citations, demonstrates his ability to balance accuracy with computational efficiency, enabling practical deployment on edge devices. He’s recognized for advancing the use of deep learning in viticulture, where his methods have set a new standard for automated yield estimation and crop monitoring. By tackling the challenges of occluded, overlapping fruits and variable lighting, He’s work not only boosts productivity but also reduces labor costs for farmers. His research bridges the gap between cutting-edge AI and real-world agricultural needs, making him a rising voice in sustainable farming technology.

Research Focus

Key Achievements

1
H-Index
1
Papers
78
Total Citations
78
Avg Citations/Paper
🏆 Most Cited Paper
Real-time tracking and counting of grape clusters in the field based on channel pruning with YOLOv5s
78 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Northwest A&F University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago