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Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings

Research Article

A Video Parallel Retrieval Method Based on Deep Hash

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  • @INPROCEEDINGS{10.1007/978-3-030-97124-3_12,
        author={Jiayi Li and Lulu Bei and Dan Li and Ping Cui and Kai Huang},
        title={A Video Parallel Retrieval Method Based on Deep Hash},
        proceedings={Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings},
        proceedings_a={SIMUTOOLS},
        year={2022},
        month={3},
        keywords={Deep hash Convolution neural network High precision},
        doi={10.1007/978-3-030-97124-3_12}
    }
    
  • Jiayi Li
    Lulu Bei
    Dan Li
    Ping Cui
    Kai Huang
    Year: 2022
    A Video Parallel Retrieval Method Based on Deep Hash
    SIMUTOOLS
    Springer
    DOI: 10.1007/978-3-030-97124-3_12
Jiayi Li1, Lulu Bei2, Dan Li2, Ping Cui2, Kai Huang3
  • 1: Transportation, Shenyang Aerospace University
  • 2: School of Information and Electrical Engineering
  • 3: JiangSu XCMG Information Technology Co., LTD.

Abstract

This paper designs a parallel video retrieval based on Spark and deep hash. The method comprises deep feature extraction using a convolution neural network based on partial semantic weighted aggregation; filtering features of image information in deep networks; the extraction and distributed storage of video summary keys; the establishment of distributed product quantitative hash coding model of image, realizing the distributed coding compression of high-dimensional features. The video parallel retrieval method proposed in this design has the advantages of high retrieval accuracy and good retrieval efficiency.

Keywords
Deep hash Convolution neural network High precision
Published
2022-03-31
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-97124-3_12
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