Yukai Zheng

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About

Yukai Zheng is advancing the frontier of precision agriculture through deep learning and robotic vision, with a focus on automated fruit harvesting. His research centers on improving the accuracy and speed of detecting apples and their stalks in unstructured orchard environments—a critical challenge for non-destructive, fully autonomous picking systems. In his highly cited 2024 work, Zheng proposed the improved YOLOv5s-GBR model, which significantly enhances apple detection in complex backgrounds, addressing the traditional trade-off between speed and accuracy. Building on this, his 2025 study introduces a dual-camera, two-stage process using an enhanced YOLOv8 network to precisely detect both apples and their stalks, enabling accurate fruit stalk cutting—a key factor in preserving post-harvest fruit quality. Though early in his career, Zheng’s work has already garnered citations for its practical impact on agricultural robotics. By integrating state-of-the-art object detection with real-world mechanical constraints, he is helping to close the gap between computer vision research and deployable harvesting technology, making him a rising voice in smart agriculture and robotic manipulation.