Zhiqi Zheng

Papers

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About

Zhiqi Zheng is a researcher at the forefront of agricultural automation and intelligent sensing technology. Their work centers on applying advanced deep learning and sensor network algorithms to solve critical problems in precision agriculture, particularly in weed management and crop protection. Zheng’s most cited study, “Application of Convolution Neural Network Algorithm Based on Intelligent Sensor Network in Target Recognition of Corn Weeder at Seedling Stage” (2022, 13 citations), makes a significant contribution by addressing a persistent challenge: grass damage in seedling corn fields. This research demonstrates how integrating convolutional neural networks with intelligent sensor networks enables precise, real-time identification of weeds, directly improving crop growth conditions and reducing insect damage. By targeting the critical seedling stage, Zheng’s work offers a practical, data-driven solution that minimizes herbicide use and enhances sustainable farming practices. Their innovative approach bridges computer vision and agronomy, showcasing how AI can transform traditional weeding into a smart, targeted operation. With growing interest in agricultural robotics and environmental sustainability, Zheng’s contributions are paving the way for more efficient, eco-friendly crop management systems.