Soad Ibrahim
Papers
1
Total Citations
2
H-Index
1
About
Soad Ibrahim is a researcher at the forefront of agricultural robotics and precision farming, with a specialized focus on computer vision and automation for greenhouse cultivation. Her work centers on developing intelligent algorithms for real-time plant structure analysis, a critical step toward fully autonomous crop management. In her most cited paper, "Automatic Detection of the Main Vine and Branches of Tomato Plants Grown in Greenhouses" (2018), Ibrahim introduced a novel algorithm that leverages the Distance Regularized Level Set Evolution (DRLSE) technique to accurately identify and track the main vine and branches of tomato plants. This method automatically locates seeding points on the main vine, enabling robust foreground tracking even in complex greenhouse environments. While her citation count (2) reflects the niche and emerging nature of her field, the practical implications of her work are significant—offering a foundation for robotic pruning, harvesting, and yield estimation. Ibrahim’s contributions are paving the way for data-driven, labor-saving solutions in controlled-environment agriculture, making her a promising voice in the intersection of computer science and sustainable food production.
Research Focus
Key Achievements
Top Papers
- 1