Yemin Guo

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About

Dr. Yemin Guo is a leading researcher in agricultural robotics and computer vision, with a primary focus on developing intelligent detection systems for fruit harvesting. His most notable contribution is the development of a lightweight YOLOv4-GhostNet network for kiwifruit detection in orchard environments, published in 2022 and garnering 17 citations. This work addresses a critical challenge in agricultural automation: enabling picking robots to accurately and rapidly identify fruit in complex, natural settings. By replacing the original CSP-Darknet53 backbone with a more efficient GhostNet architecture, Dr. Guo significantly reduced model complexity while maintaining high detection accuracy, making real-time deployment on resource-constrained robotic platforms feasible. His research bridges the gap between deep learning and practical agricultural applications, offering scalable solutions for precision farming. Dr. Guo’s work has been instrumental in advancing the field of smart agriculture, providing foundational methods that improve both the speed and reliability of automated fruit detection systems. His contributions continue to influence the development of next-generation harvesting robots, with potential applications extending to other crops and agricultural tasks.