Ruonan Yin

Shandong University of Science and Technology

Papers

Total Citations

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About

Ruonan Yin is a researcher at the forefront of agricultural robotics and intelligent perception, with a primary focus on developing efficient, real-time detection systems for automated fruit harvesting. Her most-cited work, "Fast detection method of green peach for application of picking robot" (2021, 24 citations), addresses a critical challenge in precision agriculture: accurately identifying green fruit against complex foliage backgrounds under varying lighting conditions. This contribution is pivotal for the design of vision-guided picking robots, enabling faster and more reliable fruit localization to improve harvest efficiency and reduce crop damage. By combining lightweight neural network architectures with optimized image processing pipelines, Yin’s research bridges the gap between computer vision theory and practical robotic applications. Her work has been recognized for its potential to enhance productivity in orchards, particularly for crops where color similarity between fruit and leaves poses significant detection hurdles. With a growing citation impact, Ruonan Yin continues to advance the field of agricultural automation, offering scalable solutions that support sustainable farming practices and the future of smart agriculture.