Shiyuan Li

Papers

Total Citations

H-Index

About

Shiyuan Li is a researcher at the forefront of agricultural automation and intelligent sensing technology. Their work centers on integrating advanced computational methods with sensor networks to solve critical problems in precision agriculture. Li’s most cited paper, “Application of Convolution Neural Network Algorithm Based on Intelligent Sensor Network in Target Recognition of Corn Weeder at Seedling Stage” (2022, 13 citations), exemplifies this focus. In this study, Li addresses a persistent challenge in corn cultivation: grass damage at the seedling stage, which compresses crop growth space and invites insect pests. By deploying a convolutional neural network (CNN) algorithm within an intelligent sensor network, Li developed a system capable of accurately identifying weeds for targeted removal. This contribution is vital for reducing reliance on broad-spectrum herbicides and improving crop yields. With 13 citations, the work has already garnered attention from peers in agricultural engineering and computer vision. Li’s research bridges the gap between deep learning and practical farming, offering scalable solutions for sustainable agriculture. Their innovative approach positions them as a rising voice in the field, with potential for significant future impact on automated weeding technologies.