Papers
2
Total Citations
31
H-Index
2
About
Dr. Riqing Chen is at the forefront of smart agriculture, pioneering the integration of advanced computer vision and deep learning into autonomous fruit and vegetable harvesting. His primary research focuses on developing intelligent visual perception systems that enable agricultural robots to operate with high precision in complex, unstructured field environments. Dr. Chen’s major contributions include the creation of "Pepper-YOLO," a groundbreaking lightweight model specifically designed for green pepper detection and picking point localization. This work directly addresses the critical challenge of occluded fruit and color similarity between crops and foliage, achieving robust detection without the computational burden of complex models. His comprehensive review of visual perception technology for intelligent fruit harvesting robots, garnering 16 citations, has become a foundational reference in the field, synthesizing key advancements and future directions. With his most-cited works accumulating over 30 citations in just a short span, Dr. Chen is recognized for making practical, deployable AI solutions that promise to significantly boost agricultural productivity and reduce labor dependency.
Research Focus
Key Achievements
Top Papers
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