Zainab Abuowda
Papers
1
Total Citations
4
H-Index
1
About
Zainab Abuowda is a researcher at the intersection of artificial intelligence and agricultural technology, with a primary focus on developing intelligent computer vision systems for crop management and harvesting. Her most impactful work centers on applying deep transfer learning techniques to solve practical agricultural challenges, notably demonstrated in her 2023 study on date fruit classification. In this research, Abuowda proposed an effective automated system capable of classifying both the type and maturity stage of date fruits—a critical component for designing efficient, smart robotic harvesting solutions. This work has already garnered 4 citations, reflecting its relevance to the growing field of precision agriculture. Her contributions address the pressing need for accurate, real-time visual recognition in farming, bridging the gap between advanced machine learning models and real-world agricultural applications. Abuowda’s research holds promise for enhancing food production efficiency and reducing labor dependency, making her a notable emerging voice in applied deep learning and agricultural automation.
Research Focus
Key Achievements
Top Papers
- 1Date Fruit Classification System using Deep Transfer Learning4 citations · 2023