Sujuan Hou

Shandong Normal University

Papers

2

Total Citations

141

H-Index

2

About

Dr. Sujuan Hou is a leading researcher in agricultural robotics and computer vision, specializing in intelligent fruit detection for automated harvesting systems. Her work addresses the critical challenge of recognizing green apples in complex orchard environments, where foliage, lighting variations, and occlusion make detection particularly difficult. Dr. Hou’s most influential contribution is the development of a novel green apple segmentation algorithm based on an ensemble U-Net architecture, published in 2020 and cited over 100 times—a testament to its impact on the field. This work provides a robust foundation for accurate fruit identification under natural conditions. Building on this, she introduced a fast and efficient green apple object detection model leveraging FoveaBox in 2022, which prioritizes real-time performance essential for harvesting robot vision systems. By significantly improving both speed and accuracy, Dr. Hou’s research directly enables practical applications in orchard yield measurement and autonomous fruit harvesting. Her innovative approaches continue to shape the development of smart agriculture technologies, making her a key figure in bridging deep learning with real-world agricultural automation.

Research Focus

Key Achievements

2
H-Index
2
Papers
141
Total Citations
71
Avg Citations/Paper
🏆 Most Cited Paper
A novel green apple segmentation algorithm based on ensemble U-Net under complex orchard environment
104 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Shandong Normal University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago