Haihui Zhang

Northwest A&F University

Papers

1

Total Citations

15

H-Index

1

About

Haihui Zhang is a researcher specializing in computer vision and agricultural automation, with a focus on object detection and shape analysis in natural environments. His most cited work, "Extracting the symmetry axes of partially occluded single apples in natural scene using convex hull theory and shape context algorithm" (2016, 15 citations), introduces a novel method for identifying fruit symmetry under challenging conditions like occlusion—a common issue in automated harvesting systems. By combining convex hull theory with shape context algorithms, Zhang’s approach enhances the robustness of fruit detection, directly contributing to the development of precision agriculture technologies. This work demonstrates his ability to bridge theoretical geometry with practical applications, offering solutions for real-world agricultural challenges. While his citation count reflects a growing impact in the field, Zhang’s contributions are notable for their methodological rigor and potential to improve robotic vision systems. His research sits at the intersection of computer vision, machine learning, and agricultural engineering, making him a valuable voice for students and researchers interested in applying computational techniques to biological and environmental systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Extracting the symmetry axes of partially occluded single apples in natural scene using convex hull theory and shape context algorithm
15 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Northwest A&F University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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