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Lightweight image super-resolution combining residual learning and layer attention
Image Processing | 更新时间：2024-10-09
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    • Lightweight image super-resolution combining residual learning and layer attention

    • “In the field of image super-resolution, researchers have proposed a lightweight algorithm RLAN that combines residual learning and layer attention, effectively improving the quality of image reconstruction and reducing artifacts.”
    • Chinese Journal of Liquid Crystals and Displays   Vol. 39, Issue 10, Pages: 1391-1401(2024)

    • DOI：10.37188/CJLCD.2024-0046    

      CLC： TP391.4

    • Received：18 February 2024，

      Revised：18 March 2024，

      Published：05 October 2024

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  • WU Difan, ZHANG Xuande. Lightweight image super-resolution combining residual learning and layer attention[J]. Chinese journal of liquid crystals and displays, 2024, 39(10): 1391-1401. DOI： 10.37188/CJLCD.2024-0046.

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