연구동향 분석

인공지능 기반 선체 균열 탐지 현장 적용성 연구

송상호 이갑헌 한기민 장화섭 2022년

논문상세정보
인용/피인용
' 인공지능 기반 선체 균열 탐지 현장 적용성 연구' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Artificial intelligence(인공지능)
  • Hull failure(선체 손상)
  • Object detection(객체 탐지)
  • crack(균열)
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
30 0

0.0%

' 인공지능 기반 선체 균열 탐지 현장 적용성 연구' 의 참고문헌

  • Z7 Rev.28 Hull Classification Surveys
    [2020]
  • You only learn one representation: Unified network for multiple tasks arXiv preprint arXiv:2105.04206
  • Yolov4:Optimal speed and accuracy of object detection arXiv preprint arXiv:2004.10934
  • YOLOv5
  • Vision-based corrosion detection assisted by a micro-aerial vehicle in a vessel inspection application
    Ortiz, A. [2016]
  • Recent developments in remote inspections of ship structures
    Laura Poggi [2020]
  • No.96 Double Hull Oil Tankers Guidelines for Surveys, Assessment and Repair of Hull Structures
  • ISSC Committee V.1: Damage Assessment After Accidental Events
    [2009]
  • Guidance for Remote Survey
  • Guidance for Remote Inspection Techniques
  • Detection-Based Object Tracking Applied to Remote Ship Inspection
    Jing Xie [2021]
  • Computer vision-based concrete crack detection using U-net fully convolutional networks
  • Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique