Shushuai Ma
Papers
3
Total Citations
49
H-Index
3
About
Shushuai Ma is a rising innovator at the intersection of artificial intelligence and precision agriculture, with a focused expertise in developing deep learning-based visual navigation systems for agricultural robots. His major contributions center on solving the critical challenge of autonomous crop row recognition and navigation line extraction, specifically for corn spraying robots operating under complex field conditions. Ma’s work introduces novel, lightweight neural network architectures—including YOLOv8s-CornNet and ST-YOLOv8s—that achieve high detection accuracy while maintaining real-time performance, even across different growth stages of corn. His most cited paper (24 citations) presents a navigation line extraction algorithm that integrates AI with practical robotic spraying, directly advancing smart agriculture. With additional works accumulating 16 and 9 citations, Ma’s research demonstrates tangible impact in enabling fully autonomous field operations. His achievements are particularly notable for addressing the “different growth stages” problem, a long-standing bottleneck in visual navigation, and for designing models optimized for deployment on resource-constrained robotic platforms. Shushuai Ma’s work is essential reading for researchers and engineers developing next-generation agricultural robots that must see, understand, and navigate the unpredictable farm environment.
Research Focus
Key Achievements
Top Papers
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