Ningyuan Yang
Papers
2
Total Citations
22
H-Index
2
About
Ningyuan Yang is a rising researcher in agricultural robotics and intelligent perception, focusing on the intersection of computer vision, autonomous navigation, and precision agriculture. Their work addresses critical challenges in greenhouse automation, particularly in developing robust perception systems for unstructured environments. Yang’s most cited paper, “Detection of color phenotype in strawberry germplasm resources based on field robot and semantic segmentation” (2024, 13 citations), introduces a novel approach combining field robotics with deep learning to automate phenotypic analysis, enabling high-throughput screening of strawberry varieties. This contribution has significant implications for breeding programs and crop management. Their subsequent work, “Autonomous navigation system in various greenhouse scenarios based on improved FAST-LIO2” (2025, 9 citations), advances state-of-the-art LiDAR-inertial odometry for agricultural settings, demonstrating robust localization in challenging greenhouse conditions with variable lighting and dense foliage. Yang’s research is notable for bridging the gap between theoretical robotics and practical agricultural applications, offering scalable solutions for smart farming. With a growing citation record and innovative contributions to field robotics and semantic segmentation, Yang is establishing themselves as a key figure in the next generation of agricultural automation researchers.
Research Focus
Key Achievements
Top Papers
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