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Object Segmentation Using ESRGAN and Semantic Soft Segmentation

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2023, 9(1), pp.97-104
  • DOI : 10.20465/KIOTS.2023.9.1.097
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : December 4, 2022
  • Accepted : January 8, 2023
  • Published : February 28, 2023

DongSikYoon 1 Noyoon Kwak 2

1고려대학교
2백석대학교

Accredited

ABSTRACT

This paper is related to object segmentation using ESRGAN(Enhanced Super Resolution GAN) and SSS(Semantic Soft Segmentation). The segmentation performance of the object segmentation method using Mask R-CNN and SSS proposed by the research team in this paper is generally good, but the segmentation performance is poor when the size of the objects is relatively small. This paper is to solve these problems. The proposed method aims to improve segmentation performance of small objects by performing super-resolution through ESRGAN and then performing SSS when the size of an object detected through Mask R-CNN is below a certain threshold. According to the proposed method, it was confirmed that the segmentation characteristics of small-sized objects can be improved more effectively than the previous method.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.