Guoquan Qin

South China Agricultural University

Papers

1

Total Citations

6

H-Index

1

About

Dr. Guoquan Qin is a leading researcher at the intersection of agricultural robotics and deep learning, with a primary focus on developing efficient, real-time computer vision systems for precision agriculture. His most notable contribution is the creation of Slim-Banana, a lightweight deep convolutional neural network that enables the first-ever implementation of banana detection and localization directly on edge devices. This breakthrough work, published in 2024 and already garnering 6 citations, addresses the critical challenge of deploying AI in resource-constrained, complex orchard environments. By integrating a RealSense depth sensor with Time-of-Flight technology, Dr. Qin’s system achieves precise 3D positioning, overcoming obstacles like variable lighting and occlusions. His research not only advances the field of agricultural robotics but also provides a scalable, low-complexity solution for automated fruit harvesting. Dr. Qin’s work is pivotal for students and engineers seeking to bridge the gap between cutting-edge AI and practical, real-world agricultural applications, demonstrating how efficient deep learning models can power the next generation of autonomous farm robots.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
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: 7
🏛 Institutions: South China Agricultural University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago