Abdullah Alraee
Papers
2
Total Citations
6
H-Index
2
About
Abdullah Alraee is a robotics researcher specializing in computer vision and agricultural automation, with a growing focus on deploying intelligent systems in unstructured environments. His work centers on integrating advanced perception algorithms into service robots to solve labor-intensive tasks. Alraee’s most cited paper, "Evaluating of Tree Branch Recognition Algorithm in Pruning Robots under Augmented Environmental Conditions," has garnered 4 citations and demonstrates his expertise in applying YOLOv8-seg for precise branch detection, a critical step toward automating tree pruning. This research highlights how enhanced accuracy and scalability in vision systems can revolutionize sectors like agriculture. Additionally, his work on "Efficient Ball Position Estimation for Tennis Court Robot Assistants using a Dual-Camera System" (2 citations) addresses the practical challenge of ball collection in professional tennis, proposing a mobile robot solution that saves time and effort. By tackling both agricultural and sports robotics, Alraee showcases a versatile approach to real-world automation. His contributions are particularly notable for their focus on robust performance under augmented or variable conditions, making his findings valuable for students and researchers interested in the intersection of computer vision, robotics, and applied AI.
Research Focus
Key Achievements
Top Papers
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- 2