Xinyang Mu
Papers
4
Total Citations
75
H-Index
4
About
Xinyang Mu is a leading researcher in precision agricultural robotics, with a core focus on automating apple orchard management through advanced computer vision and robotic systems. Her work directly addresses the critical challenge of crop load management—the single most important factor for orchard profitability. Mu’s major contribution lies in developing deep learning-based methods for the precise identification of individual apple flowers, particularly the "king flower," whose central position within a cluster often leads to occlusion by lateral flowers. Her most cited paper, "Mask R-CNN based apple flower detection and king flower identification for precision pollination" (2022, 60 citations), established a foundational method for this task, enabling targeted robotic pollination. Building on this, she has engineered an advanced Cartesian robotic spraying system for precision chemical thinning, as detailed in her 2023 work (5 citations). By integrating detection, localization, and a communication algorithm for end-effector positioning, Mu’s research bridges the gap between AI-driven perception and physical robotic action, directly impacting the efficiency of pollination and thinning—two key aspects of effective crop load management. Her work is pivotal for the future of sustainable, data-driven agriculture.
Research Focus
Key Achievements
Top Papers
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