Rui‐Sheng Jia

Shandong University of Science and Technology

Papers

Total Citations

177

H-Index

About

Rui‐Sheng Jia is a leading researcher in agricultural robotics, specializing in computer vision and deep learning for fruit and vegetable detection in complex, real-world environments. His work directly addresses the critical challenge of enabling picking robots to accurately identify produce under difficult conditions—such as backlighting, direct sunlight, overlapping fruit, and occluding leaves—that have long hindered automation in agriculture. Jia’s most impactful contributions include the development of fast, efficient detection algorithms optimized for embedded platforms. His highly cited paper “Light-YOLOv3: fast method for detecting green mangoes in complex scenes using picking robots” (73 citations) introduced a lightweight variant of the YOLOv3 architecture, dramatically reducing computational overhead while maintaining detection accuracy. Similarly, his work on “Fast Method of Detecting Tomatoes in a Complex Scene for Picking Robots” (66 citations) tackled the dual problems of scene complexity and the limited computing power of on-board embedded devices. He has also extended these methods to green peaches and non-contact ball detection, consistently demonstrating how to balance speed, accuracy, and energy efficiency. With over 177 total citations across his most-cited works, Jia’s research has become foundational for engineers developing practical, deployable picking robots. His innovations are paving the way for more robust, cost-effective automation in agriculture, directly impacting the future of food production.