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    Automatic Terrain Debris Recognition Network Based on 3D Remote Sensing Data

    Xu Han1, #, Huijun Yang1, 4, *, Qiufeng Shen1, #, Jiangtao Yang2, Huihui Liang1, Cancan Bao1, Shuang Cang3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 579-596, 2020, DOI:10.32604/cmc.2020.011262

    Abstract Although predecessors have made great contributions to the semantic segmentation of 3D indoor scenes, there still exist some challenges in the debris recognition of terrain data. Compared with hundreds of thousands of indoor point clouds, the amount of terrain point cloud is up to millions. Apart from that, terrain point cloud data obtained from remote sensing is measured in meters, but the indoor scene is measured in centimeters. In this case, the terrain debris obtained from remote sensing mapping only have dozens of points, which means that sufficient training information cannot be obtained only through the convolution of points. In… More >

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