Yuancheng Xu
Papers
1
Total Citations
62
H-Index
1
About
Yuancheng Xu is a leading researcher in precision agriculture and computer vision, with a focus on intelligent weed detection and crop monitoring. His most cited work, "Weed Detection in Images of Carrot Fields Based on Improved YOLO v4" (2021, 62 citations), introduces a lightweight adaptation of the YOLO v4 architecture, enabling accurate, real-time identification of multiple weed species in carrot fields. This contribution directly addresses a critical bottleneck in precision weed control, offering a scalable, machine vision–based solution that reduces reliance on herbicides. Xu’s research bridges deep learning and agronomy, demonstrating how optimized neural networks can be deployed in resource-constrained agricultural settings. His work has been widely recognized for its practical impact, with the 2021 paper serving as a foundational reference for subsequent studies in field-level weed detection. By advancing lightweight, high-accuracy models, Xu is helping to pave the way for autonomous, data-driven farming systems that enhance both productivity and environmental sustainability.
Research Focus
Key Achievements
Top Papers
- 1Weed Detection in Images of Carrot Fields Based on Improved YOLO v462 citations · 2021