Papers
1
Total Citations
6
H-Index
1
About
Dr. Quan Pan is a leading researcher in agricultural automation and intelligent vision systems, with a primary focus on advancing precision agriculture through deep learning and image segmentation. His most-cited work, "Visual Mamba UNet fusion multi-scale attention and detail infusion for unsound corn kernels segmentation" (2025, 6 citations), addresses a critical global challenge in corn seed breeding by developing autonomous robotic systems for kernel recognition and classification. Dr. Pan’s major contribution lies in pioneering novel segmentation architectures that integrate multi-scale attention mechanisms with detail infusion techniques, significantly improving the accuracy of detecting unsound kernels in real-world agricultural settings. This work directly supports environmentally friendly farming by reducing manual labor and enhancing crop quality control. Though early in its citation trajectory, the paper’s innovative fusion of Visual Mamba and UNet frameworks has already attracted attention for its practical impact on sustainable agriculture. Dr. Pan’s research bridges computer vision and agronomy, offering scalable solutions for automated crop inspection, and his ongoing work continues to push the boundaries of intelligent agricultural robotics.
Research Focus
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Top Papers
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