Zainab Mohammed Amean
Papers
1
Total Citations
13
H-Index
1
About
Zainab Mohammed Amean is a researcher at the intersection of computer vision and precision agriculture, whose work focuses on automating plant analysis to boost agricultural efficiency. Her key research areas include image segmentation, machine vision, and robotic perception for plant phenotyping. Her most cited work, "Automatic Plant Branch Segmentation and Classification Using Vesselness Measure" (2013), introduced a novel approach that leverages vesselness filters—typically used in medical imaging—to accurately identify and classify plant branches and stems from visual data. This method enables mobile robots and automated systems to distinguish between leaves, stems, and branches, a critical step for non-invasive monitoring of plant health and growth. With 13 citations, this foundational paper has influenced subsequent studies in agricultural robotics and plant phenotyping. Amean’s contributions are particularly notable for bridging biomedical imaging techniques with agricultural challenges, demonstrating how cross-disciplinary methods can solve practical problems in modern farming. Her work continues to support the development of intelligent systems that save time and improve production efficiency in agriculture.
Research Focus
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Top Papers
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