Xuechen Li

Papers

Total Citations

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About

Xuechen Li is a leading researcher in agricultural robotics and precision weed management, with a focus on integrating deep learning and intelligent control systems. Their most cited work, "An Intelligent Robot Based on Optimized YOLOv11l for Weed Control in Lettuce" (2025), has already garnered 13 citations, reflecting its timely impact on sustainable farming. Li’s major contributions lie in developing real-time, vision-guided robotic systems that replace labor-intensive or chemical-dependent weed control methods. By optimizing the YOLOv11l object detection architecture, they achieved high-accuracy, low-latency weed recognition, enabling effective intra-row weeding in lettuce crops. This work addresses critical challenges—rising labor costs, herbicide environmental risks, and the prohibitive expense of laser systems—by offering a scalable, cost-effective automation solution. Li’s research bridges computer vision, robotics, and agronomy, demonstrating how deep learning can be deployed on embedded hardware for field applications. Their achievements highlight a commitment to practical, environmentally friendly agricultural technologies, positioning them as an emerging voice in precision agriculture. For students and researchers, Li’s work exemplifies how targeted algorithmic optimization can translate into real-world impact, advancing both the science and practice of intelligent farming.