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    Design of Pixel Compensation Algorithm for Video Image Based on Local Convolution
    ZHA Huaizhi
    Journal of Jishou University(Natural Sciences Edition)    2023, 44 (6): 1-8.   DOI: 10.13438/j.cnki.jdzk.2023.06.001
    Abstract105)      PDF(pc) (3962KB)(131)       Save
    A video image pixel compensation method based on local convolution (local convolution compensation) is proposed to repair missing pixels in high-speed moving targets.The method introduces local convolution to segment the neural network model and reconstruct video image frames.It activates the source video image and its corresponding pixel space,applies linear mean compensation to fill the interpolated frame holes in the video image,and evaluates the matching degree of the video image to complete the pixel compensation.Comparative experimental results show that the average gradient of the local convolution compensation method is 11.239,significantly higher than the other three comparative methods,which indicates that the video image after compensation using the local convolution method has higher clarity.
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    Community Detection Algorithm for Bipartite Networks Based on Spectral Clustering
    LIU Chenchen, XU Ying
    Journal of Jishou University(Natural Sciences Edition)    2023, 44 (6): 9-13.   DOI: 10.13438/j.cnki.jdzk.2023.06.002
    Abstract118)      PDF(pc) (676KB)(135)       Save
    In order to solve the problem of low precision and original network information lose in community detection of bipartite network,a new spectral clustering algorithm named SVD-MS is proposed.This method maps Barber's problem of maximizing the module size of bipartite networks to the problem of singular value vector decomposition,and combines heuristic algorithms to quickly solve vector partitioning problems.Experimental results show that,the SVD-MS algorithm can effectively partition the community structure of bipartite networks and preserve the original network information.
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