Endogenous dynamic defense architecture-based multi-objective service function chain deployment method

    公开(公告)号:US12003528B1

    公开(公告)日:2024-06-04

    申请号:US18581424

    申请日:2024-02-20

    IPC分类号: H04L9/40

    CPC分类号: H04L63/1433 H04L63/1441

    摘要: An endogenous dynamic defense architecture-based multi-objective service function chain deployment method solves a problem of multi-objective deployment by constructing an endogenous dynamic defense architecture, in which a basic mode includes using moving target defense to ensure the security of VNFs, and an enhanced mode includes using mimic defense to perform security protection on the VNFs; in a construction module, a sub-pool division algorithm is proposed to divide a heterogeneous replica pool into a plurality of sub-pools, and VNFs are selected from the sub-pools so as to constitute a heterogeneous replica set; in a scheduling module, a replica VNF dynamic scheduling deployment algorithm is proposed, a deployment set is selected from the heterogeneous replica set for deployment, and is sent to a processing module; the input module replicas an input and distributes same to the processing module.

    SEMANTIC SEGMENTATION METHOD AND SYSTEM FOR REMOTE SENSING IMAGE FUSING GIS DATA

    公开(公告)号:US20220092368A1

    公开(公告)日:2022-03-24

    申请号:US17144256

    申请日:2021-01-08

    发明人: Jie Hao Yuhang Gu

    摘要: The present disclosure relates to a semantic segmentation method and system for a remote sensing image fusing GIS data. The method includes: obtaining a first remote sensing data training set and first GIS data; preprocessing the first remote sensing data training set to obtain a second remote sensing data training set; preprocessing the first GIS data based on the second remote sensing data training set to obtain second GIS data; performing data enhancement on the second remote sensing data training set to obtain a third remote sensing data training set; training a semantic segmentation model based on the third remote sensing data training set and the second GIS data; and performing semantic segmentation on the remote sensing image to be segmented based on the first GIS data and the trained semantic segmentation model to obtain a semantic set.

    Semantic segmentation method and system for remote sensing image fusing GIS data

    公开(公告)号:US11488403B2

    公开(公告)日:2022-11-01

    申请号:US17144256

    申请日:2021-01-08

    发明人: Jie Hao Yuhang Gu

    摘要: The present disclosure relates to a semantic segmentation method and system for a remote sensing image fusing GIS data. The method includes: obtaining a first remote sensing data training set and first GIS data; preprocessing the first remote sensing data training set to obtain a second remote sensing data training set; preprocessing the first GIS data based on the second remote sensing data training set to obtain second GIS data; performing data enhancement on the second remote sensing data training set to obtain a third remote sensing data training set; training a semantic segmentation model based on the third remote sensing data training set and the second GIS data; and performing semantic segmentation on the remote sensing image to be segmented based on the first GIS data and the trained semantic segmentation model to obtain a semantic set.

    Road Recognition Method and System Based on Seed Point

    公开(公告)号:US20220092314A1

    公开(公告)日:2022-03-24

    申请号:US17145193

    申请日:2021-01-08

    发明人: Jie Hao Lei Zhang

    摘要: The present disclosure relates to a road recognition method and system based on a seed point. The method includes: obtaining a remote sensing image; obtaining a grayscale image; inserting a seed point in the grayscale image; searching for four initial road boundary points using the seed point as a reference point; obtaining a smallest bounding rectangle search box formed by the four initial road boundary points; obtaining a plurality of candidate search boxes based on the obtained search boxes; determining whether a sum of squares of grayscale differences between the plurality of candidate search boxes and the obtained search box is greater than a preset threshold; and if yes, stopping searching and completing road recognition; or if not, selecting a new search box from the plurality of candidate search boxes, and retrieving a plurality of candidate search boxes based on the new search box.