Lele Wang

South China Agricultural University

Papers

1

Total Citations

41

H-Index

1

About

Lele Wang is a leading researcher in agricultural robotics and computer vision, with a primary focus on precision detection for automated fruit harvesting. Her most influential work, "Precision Detection of Dense Plums in Orchards Using the Improved YOLOv4 Model" (2022), has garnered 41 citations and addresses a critical bottleneck in agricultural automation: the reliable identification of small, densely clustered fruits. By enhancing the YOLOv4 deep learning architecture, Wang developed a method that significantly improves recognition accuracy for plums—a notoriously challenging target due to their compact size and overlapping growth patterns. This contribution directly supports the visual perception systems of agricultural picking robots, enabling more efficient and damage-free harvesting. Wang’s research bridges the gap between state-of-the-art object detection and real-world orchard conditions, offering practical solutions for precision agriculture. Her work is widely recognized for its impact on reducing manual labor and increasing yield efficiency, making her a key figure in the advancement of smart farming technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
41
Total Citations
41
Avg Citations/Paper
🏆 Most Cited Paper
Precision Detection of Dense Plums in Orchards Using the Improved YOLOv4 Model
41 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: South China Agricultural University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago