Zhihua Xie

South China Agricultural University, Jiangxi Science and Technology Normal University

Papers

Total Citations

164

H-Index

About

Zhihua Xie’s research lies at the intersection of agricultural robotics and computer vision, with a focus on developing intelligent systems for precision harvesting and autonomous navigation. His most impactful work, “Semantic Segmentation of Litchi Branches Using DeepLabV3+ Model” (2020), has garnered 162 citations, addressing a critical challenge in fruit-picking robotics: accurately detecting small, easily damaged litchi branches for robotic clamping and cutting. By leveraging a fully convolutional neural network, Xie’s approach significantly improves branch segmentation accuracy, enabling safer, more efficient automated harvesting. This contribution directly supports the advancement of agricultural automation, reducing crop damage and labor dependency. Additionally, his earlier work on “Real time target tracking based on nonlinear mean shift and particle filters” (2017) explores robust filtering methods for radar tracking, video surveillance, and robot vision, estimating target motion parameters like position and velocity. Though less cited, this foundational research demonstrates his versatility in real-time tracking systems. Xie’s achievements highlight his role in bridging deep learning with practical agricultural applications, offering scalable solutions for smart farming. His work continues to inspire researchers in robotic perception and precision agriculture, emphasizing the transformative potential of AI in food production.