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Object Detection for Unsupervised Domain Adaptation with Pseudo labeling

  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 권호(발행년)
    The 7th International Conference on Next Generation Computing 2021 (2021.11) 바로가기
  • 페이지
    pp.326-327
  • 저자
    Joonhwan Han, Wonjun Hwang
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A448086

원문정보

초록

영어
Unsupervised Domain Adaptation of object detection can prevent performance degradation for new environment which does not include annotation We improved the performance by applying Pseudo label.

목차

Abstract
I. INTRODUCTION
II. RELATED WORK
A. Unsupervised Domain Adaptation
B. Pseudo Label
III. METHOD
A. Loss for pseudo label
B. Discriminator
IV. EXPERIMENTS
A. Implementation Details
B. Result
V. CONCULUSION
ACKNOWLEDGMENT
REFERENCES

저자

  • Joonhwan Han [ Department of Artificial Intelligence Ajou Univ. ]
  • Wonjun Hwang [ Department of Artificial Intelligence Ajou Univ. ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국차세대컴퓨팅학회 학술대회
    • 간기
      반년간
    • 수록기간
      2021~2025
    • 십진분류
      KDC 566 DDC 004