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    Topography-Enhanced Multilevel Residual Attention U-Net Model for Sea Ice Concentration Spatial Super-Resolution Prediction by Jianxin He, Yuxin Zhao, Shuo Yang, Haoyu Wang, Xiong Deng

    Published 2025-01-01
    “…Experimental results indicate that, in the pan-Arctic region, TE-MRAU-Net outperforms other models in various evaluation metrics and spatial distribution reconstruction. For the 5&#x00D7; SR prediction task, the model achieves a mean absolute error of 0.0049, a root-mean-square error of 0.0081, a correlation coefficient (<inline-formula><tex-math notation="LaTeX">$r$</tex-math></inline-formula>) of 0.9993, a peak signal-to-noise ratio of 40.21 dB, a structural similarity index measure of 0.9764, a balanced accuracy of 0.9428, a mean opinion score of 4.63, and a subjective image quality assessment of 9.75, greatly enhancing the model&#x2019;s ability to capture detailed SIC features.…”
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