Yu Qi

South China Agricultural University

Papers

1

Total Citations

141

H-Index

1

About

Yu Qi is a leading researcher in agricultural automation and computer vision, with a focus on precision fruit detection and maturity classification. Her most-cited work, "Detection of passion fruits and maturity classification using Red-Green-Blue Depth images" (2018, 141 citations), introduced a pioneering method that leverages RGB-D imaging to accurately identify and assess the ripeness of passion fruits in complex orchard environments. This contribution has significantly advanced non-destructive harvesting technologies, enabling more efficient and data-driven agricultural practices. Qi’s research bridges the gap between machine learning and real-world farming applications, offering scalable solutions for crop monitoring and yield estimation. Her work has been widely adopted by researchers in precision agriculture, as evidenced by its strong citation record, and has influenced subsequent studies on fruit detection using depth sensors. By combining robust image processing with practical agricultural needs, Yu Qi has established herself as a key innovator in smart farming, with her findings directly supporting the development of autonomous harvesting systems and sustainable food production.

Research Focus

Key Achievements

1
H-Index
1
Papers
141
Total Citations
141
Avg Citations/Paper
🏆 Most Cited Paper
Detection of passion fruits and maturity classification using Red-Green-Blue Depth images
141 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: South China Agricultural University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago