반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

YOLOv8을 이용한 화재 검출 시스템 개발

Development of Fire Detection System using YOLOv8

  • 이채은 (성균관대학교 실감미디어공학과) ;
  • 박천수 (성균관대학교 컴퓨터교육과)
  • Chae Eun Lee (Immersive Media Engineering, Sungkyunkwan University) ;
  • Chun-Su Park (Computer Education, Sungkyunkwan University)
  • 투고 : 2024.01.08
  • 심사 : 2024.03.20
  • 발행 : 2024.03.31
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초록

It is not an exaggeration to say that a single fire causes a lot of damage, so fires are one of the disaster situations that must be alerted as soon as possible. Various technologies have been utilized so far because preventing and detecting fires can never be completely accomplished with individual human efforts. Recently, deep learning technology has been developed, and fire detection systems using object detection neural networks are being actively studied. In this paper, we propose a new fire detection system that improves the previously studied fire detection system. We train the YOLOv8 model using refined datasets through improved labeling methods, derive results, and demonstrate the superiority of the proposed system by comparing it with the results of previous studies.

키워드

과제정보

본 연구는 중소벤처기업부의 연구비지원(00264489)에 의해 수행되었습니다. 이 논문은 2023년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구입니다. (No.RS-2023-00254129, 메타버스융합대학원(성균관대학교))

참고문헌

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