지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- 한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2015 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.7 No.1
- 발행연도
- 2015.6
- 수록면
- 194 - 197 (4page)
이용수
초록· 키워드
오류제보하기
As the methods using UAV(Unmanned Aerial Vehicles) are being sought in the multipurpose surveillance and monitoring technologies such as lifesaving. Collection of the weather information, the forest fire prevention, etc, the active researches are under progress in various areas. In this paper, using a miniature UAV, to provide an image processing system of the structure cracks situational awareness for the safety inspection of the structure. The structures for seasonal changes greatly depending on the time each day, there is a difficult problem to check for damage. Using the context-aware image processing system for the image that is suspicious of having cracks, it is possible to find out whether the structure gets damaged and take an immediate action if necessary. Ultimately it could contribute to risk reduction. Context-aware crack image processing system processes the image that seems to have cracks and analyzes the data sent by a number of sensors, so as to establish an optimal condition. The proposed system enables to accurately detect the defects occurring at the surface of facility and contributes to saving of time and efforts effectively.
목차
Abstract
I. INTRODUCTION
II. RELATED WORKS
III. CONTEXT-AWARE IMAGE PROCESSING SYSTEM USING SMALL UAV FOR RECOGNIZING CRACKS ON HIGH-RISE STRUTURE
IV. CONCLUSIONS
REFERENCES
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
딥러닝 및 영상처리 기술을 활용한 콘크리트 균열 검출 방법
대한건축학회 논문집 - 구조계
2019 .11
-
무인기 기반의 교량 균열 탐지를 위한 타당성 연구
한국소음진동공학회논문집
2018 .02
-
An active learning method with difficulty learning mechanism for crack detection
Smart Structures and Systems, An International Journal
2022 .01
-
Real-time comprehensive image processing system for detecting concrete bridges crack
Computers and Concrete, An International Journal
2019 .01
-
건물 안전 진단을 위한 딥러닝 기반의 외벽 균열 검출 방법
대한설비관리학회지
2021 .12
-
Comparative study on cracked beam with different types of cracks carrying moving mass
Structural engineering and mechanics : An international journal
2015 .01
-
A Robust Crack Filter Based on Local Gray Level Variation and Multiscale Analysis for Automatic Crack Detection in X-ray Images
Journal of Electrical Engineering & Technology
2016 .07
-
Crack growth prediction on a concrete structure using deep ConvLSTM
Smart Structures and Systems, An International Journal
2024 .04
-
SAT 운용을 위한 세라믹의 미세 크랙 판별 소프트웨어 개발
대한산업공학회 춘계공동학술대회 논문집
2015 .04
-
A deep learning-based vision enhancement method for UAV assisted visual inspection of concrete cracks
Smart Structures and Systems, An International Journal
2021 .01
-
UAV-based bridge crack discovery via deep learning and tensor voting
Smart Structures and Systems, An International Journal
2024 .02
-
Experimental and Numerical Investigations on Crack Intersection and Propagation of Concrete Structures
International Journal of Concrete Structures and Materials
2023 .03
-
The investigation crack problem through numerical analysis
Structural Engineering and Mechanics, An Int＇l Journal
2016 .01
-
SAMT: Shape-aware Multi-task Deep Convolutional Model for Crack Identification
대한전자공학회 학술대회
2023 .06
-
전자식 균열 측정 기기를 이용한 빅데이터 기반 균열 분석
대한건축학회 학술발표대회 논문집
2024 .10
-
Crack analysis of reinforced concrete members with and without crack queuing algorithm
Structural Engineering and Mechanics, An Int＇l Journal
2019 .01
-
드론 활용 교량 안전점검을 위한 딥러닝 균열 분석에 관한 연구
한국정보기술학회논문지
2021 .12
-
역학적 파동을 이용한 콘크리트 내부 수직균열 탐사 시스템
대한건축학회 학술발표대회 논문집
2022 .10
-
딥러닝과 영상처리기법을 이용한 콘크리트 지반 구조물 균열 탐지
한국지반공학회논문집
2018 .12
-
Automated Detection of Surface Cracks and Numerical Correlation with Thermal‑Structural Behaviors of Fire Damaged Concrete Beams
International Journal of Concrete Structures and Materials
2020 .05
이 논문의 저자 정보
이 논문과 함께 이용한 논문
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-ECN-0101-2018-004-000971123