Sami Hassan Ahmed Mohamed
Papers
1
Total Citations
42
H-Index
1
About
Dr. Sami Hassan Ahmed Mohamed is a leading researcher in precision agriculture and intelligent automation, with a primary focus on non-destructive plant phenotyping and robotic transplanting systems. His most impactful work introduces an innovative seedling-lump integrated monitoring approach that leverages Intel RealSense depth cameras to automatically assess plant growth parameters without damaging delicate seedlings—a critical advancement for high-throughput greenhouse automation. This seminal 2019 paper has garnered 42 citations, reflecting its practical significance in bridging computer vision and agricultural robotics. Dr. Mohamed’s contributions extend to developing real-time, image-based solutions that replace manual inspection, enabling fully automatic transplanting with enhanced accuracy and efficiency. His research sits at the intersection of agricultural engineering, sensor fusion, and machine learning, addressing key bottlenecks in modern farming. By integrating depth-sensing technology with growth monitoring, he has provided a scalable framework for smart agriculture that reduces labor costs and improves crop uniformity. Dr. Mohamed’s work is widely recognized for its direct applicability in commercial nurseries and controlled-environment agriculture, positioning him as a key innovator in the field of precision horticulture.
Research Focus
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Top Papers
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