Laser & Optoelectronics Progress, Volume. 62, Issue 8, 0815006(2025)

Improved RRU-Net for Image Splicing Forgery Detection

Ying Ma1、*, Yilihamu Yaermaimaiti1, Shuoqi Cheng1, and Yazhou Su2
Author Affiliations
  • 1School of Electrical Engineering, Xinjiang University, Urumqi 830017, Xinjiang , China
  • 2State Grid Xinjiang Electric Power Co., Ltd., Marketing Service Center, Urumqi 830013, Xinjiang , China
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    References(25)

    [3] Li X R, Chen J J, Wang M T et al. Advancement in structured illumination microscopy based on deep learning[J]. Chinese Journal of Lasers, 51, 2107103(2024).

    [12] Pan W D, Li A H, Liu X S. Progress in research and application of image stitching technology based on regional optimization[J]. Laser & Optoelectronics Progress, 61, 1800004(2024).

    [14] Hu B, Zhang Z J. RGB-D image superpixel segmentation algorithm based on edge information[J]. Computer Era, 111-115(2023).

    [18] Li H Y, Xu B Q, Zhang Z Y et al. Small target detection in remote sensing images based on global context information[J]. Acta Optica Sinica, 44, 2428004(2024).

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    Ying Ma, Yilihamu Yaermaimaiti, Shuoqi Cheng, Yazhou Su. Improved RRU-Net for Image Splicing Forgery Detection[J]. Laser & Optoelectronics Progress, 2025, 62(8): 0815006

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    Paper Information

    Category: Machine Vision

    Received: Jul. 9, 2024

    Accepted: Oct. 8, 2024

    Published Online: Mar. 21, 2025

    The Author Email:

    DOI:10.3788/LOP241655

    CSTR:32186.14.LOP241655

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