Yingqi Peng

Papers

Total Citations

H-Index

About

Yingqi Peng is a researcher focused on agricultural robotics and machine vision, with a particular emphasis on intelligent fruit recognition systems for automated harvesting. Their most cited work, “Citrus Recognition in Real Scenarios Based on Machine Vision” (2019, 4 citations), addresses a critical bottleneck in agricultural automation: the accurate detection and localization of citrus fruits in complex, natural environments. This research is foundational for developing fruit-harvesting robots, aiming to replace inefficient, high-cost manual labor with precise, vision-guided automation. By tackling challenges such as variable lighting, occlusions, and background clutter, Peng’s contributions advance the practical deployment of machine vision in precision agriculture. While their citation count reflects an emerging career, the work’s direct relevance to the growing field of agricultural robotics underscores its potential impact. Peng’s research bridges computer vision and agricultural engineering, offering scalable solutions to labor shortages in fruit harvesting. For students and researchers exploring smart farming technologies, Peng’s work provides a clear example of how machine vision can transform traditional agricultural practices into data-driven, automated systems.