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  1. No Access

    Article

    A novel lightweight multi-dimension feature fusion network for single-image super-resolution reconstruction

    In recent years, due to the powerful feature extraction capabilities of convolutional neural networks (CNNs), many single-image super-resolution (SISR) methods based on CNN have achieved remarkable results. Ho...

    **aoxin Guo, Zhenchuan Tu, Guangyu Li, Zhengran Shen, Weijia Wu in The Visual Computer (2024)

  2. No Access

    Article

    Graph alternate learning for robust graph neural networks in node classification

    The real-world graphs are full of noises and perturbation. However, recent studies show that the existing graph neural networks (GNNs) are usually sensitive to the quality of the input graph. In this work, we ...

    Baoliang Zhang, **aoxin Guo, Zhenchuan Tu, Jia Zhang in Neural Computing and Applications (2022)