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A Target Detection Algorithm based on Single Shot Detector

Single Shot Detector 기반 타깃 검출 알고리즘

  • Feng, Yuanlin (Department of Computer Science, Hanynag University) ;
  • Joe, Inwhee (Department of Computer Science, Hanynag University)
  • 풍원림 (한양대학교 컴퓨터소프트웨어학과) ;
  • 조인휘 (한양대학교 컴퓨터소프트웨어학과)
  • Published : 2021.05.12

Abstract

In order to improve the accuracy of small target detection more effectively, this paper proposes an improved single shot detector (SSD) target detection and recognition method based on cspdarknet53, which introduces lightweight ECA attention mechanism and Feature Pyramid Network (FPN). First, the original SSD backbone network is replaced with cspdarknet53 to enhance the learning ability of the network. Then, a lightweight ECA attention mechanism is added to the basic convolution block to optimize the network. Finally, FPN is used to gradually fuse the multi-scale feature maps used for detection in the SSD from the deep to the shallow layers of the network to improve the positioning accuracy and classification accuracy of the network. Experiments show that the proposed target detection algorithm has better detection accuracy, and it improves the detection accuracy especially for small targets.

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