Papers
11
Total Citations
202
H-Index
8
About
Mustafa Mhamed is a prolific researcher specializing in agricultural robotics, precision automation, and deep learning applications for smart farming. His work centers on advancing the mechanization of labor-intensive horticultural operations, with a particular focus on apple orchard automation, robotic harvesting systems, and autonomous pollination technologies. Mhamed's most influential contributions include comprehensive reviews of apple harvesting robotics, with his 2024 survey on automated orchard equipment accumulating 70 citations, establishing it as a key reference in the field. His research rigorously evaluates how deep learning surpasses traditional computer vision algorithms in fruit detection, and how multi-source sensor fusion enables precise apple localization — insights critical to building practical, deployable systems. His 2025 review on autonomous flower pollination, alongside a lightweight YOLOv5s-Im model for drone-based apple flower detection, demonstrates his commitment to bridging theoretical advances with real-world agricultural deployment. Beyond apples, Mhamed extends his expertise to corn disease monitoring, yield prediction, cucumber picking robotics, and IoT-integrated farming systems, reflecting a broad vision for intelligent, end-to-end agricultural automation. With over 180 cumulative citations across recent publications, his rapidly growing impact positions him as an emerging leader shaping the future of smart, sustainable orchard and crop management technologies.
Research Focus
Key Achievements
Top Papers
- 1Advances in apple’s automated orchard equipment: A comprehensive research70 citations · 2024
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