Zilin Xia
Papers
4
Total Citations
110
H-Index
4
About
Zilin Xia is a leading researcher in agricultural robotics and computer vision, with a primary focus on developing intelligent systems for automated fruit harvesting. Their work centers on improving the accuracy and speed of apple detection and localization—a critical bottleneck in the deployment of picking robots. Xia’s major contributions include pioneering the integration of improved deep learning models, such as YOLOX and SOLOv2, with RGB-D imaging to achieve real-time, high-precision fruit recognition. Their 2023 paper on an improved YOLOX method, cited over 75 times across two versions, demonstrates a significant reduction in model complexity while maintaining detection speed suitable for harvesting robots. In 2024, Xia advanced this work with a high-precision apple recognition and localization method using SOLOv2 instance segmentation, which has already garnered 25 citations. Additionally, their research on combining image segmentation with point cloud registration for sensing obscured tree branches addresses a key challenge in unstructured orchard environments. Xia’s cumulative citation impact—exceeding 110 citations in just two years—underscores the practical relevance of their contributions to the field of precision agriculture and intelligent robotics.
Research Focus
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Top Papers
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