Shike Zhai

Papers

Total Citations

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About

Shike Zhai is a leading researcher in agricultural robotics and computer vision, with a focus on intelligent fruit recognition systems for automated harvesting. His most cited work, a 2022 study on lightweight detection algorithms for kiwifruit, has garnered 35 citations and addresses a critical bottleneck in precision agriculture: the need for efficient, real-time object detection on resource-constrained mobile devices. Zhai’s key contribution lies in enhancing the YOLOX-S architecture to overcome challenges posed by small-scale, low-feature fruit targets in complex orchard environments. By optimizing the algorithm for speed and accuracy, his research enables picking robots to identify kiwifruit with greater reliability, even under variable lighting and occlusion conditions. This work exemplifies his broader expertise in deep learning, embedded systems, and agricultural automation. Zhai’s innovations have direct implications for reducing labor costs and improving harvest efficiency, making him a notable figure in the intersection of AI and sustainable farming. His ongoing efforts continue to push the boundaries of lightweight neural networks for real-world agricultural applications.