Target detection in remote sensing image based on deep learning

DOI
  • Zhao Lianchen
    College of Electronic Information and Automation, Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology
  • Peng Yizhun
    College of Electronic Information and Automation, Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology
  • Li Di
    College of Electronic Information and Automation, Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology
  • Zhang Yuheng
    College of Electronic Information and Automation, Tianjin University of Science and Technology Advanced Structural Integrity International Joint Research Centre, Tianjin University of Science and Technology

Description

For high-resolution optical remote sensing images, there are still many challenges in target detection. In this paper, deep learning algorithm is used to detect the target in remote sensing image. Improve and optimize the deep learning target detection algorithm. When the selected data set is used for target detection, the AP value is improved, which leads to the concept of multi-scale feature fusion feature pyramid and residual network. By improving the selected Yolov3 network model, the detection effect of the two targets of aircraft and ships in remote sensing images has been significantly improved.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390851175703302784
  • DOI
    10.5954/icarob.2021.os3-4
  • ISSN
    21887829
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
  • Abstract License Flag
    Disallowed

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