• 제목/요약/키워드: 삼육건축

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회원작품

  • 대한건축사협회
    • 건축사
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    • 3호통권121호
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    • pp.35-49
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    • 1979
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회원작품

  • 대한건축사협회
    • 건축사
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    • 제5권10호통권26호
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    • pp.21-41
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    • 1970
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회원작품

  • 대한건축사협회
    • 건축사
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    • 제5권11호통권27호
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    • pp.21-42
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    • 1970
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회원작품

  • 대한건축사협회
    • 건축사
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    • 3호통권53호
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    • pp.34-39
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    • 1973
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회원작품

  • 대한건축사협회
    • 건축사
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    • 7호통권67호
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    • pp.51-61
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    • 1974
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아파트 건설 현장 작업자 특징 추출 및 다중 객체 추적 방법 제안 (A Suggestion for Worker Feature Extraction and Multiple-Object Tracking Method in Apartment Construction Sites)

  • 강경수;조영운;류한국
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2021년도 봄 학술논문 발표대회
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    • pp.40-41
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    • 2021
  • The construction industry has the highest occupational accidents/injuries among all industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. Therefore, this study proposed to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple-object tracking with instance segmentation. To evaluate the system's performance, we utilized the MS COCO and MOT challenge metrics. These results present that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

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건설 현장 CCTV 영상에서 딥러닝을 이용한 사물 인식 기초 연구 (A Basic Study on the Instance Segmentation with Surveillance Cameras at Construction Sties using Deep Learning based Computer Vision)

  • 강경수;조영운;류한국
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2020년도 가을 학술논문 발표대회
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    • pp.55-56
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    • 2020
  • The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.

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AHP를 활용한 아름다운 장소 이미지의 중요도 인식 분석 (Analysis on the Importance of Beautiful Place Images Recognition Using AHP)

  • 이임정;조치웅;노경란
    • 한국농촌건축학회논문집
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    • 제24권2호
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    • pp.1-11
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    • 2022
  • Purpose: The purpose of this study is to analyze image factors of places located in natural and humanistically superior geographical locations. It aims to analyze image recognition and spatiality of scenically historical Sahmyook University, located northeast of Gangneung, through standardization. Method: The analysis method of landscape is composed of data investigation and research, and elements of how students, faculty, and visitors recognize a place's beautiful image will be examined. Result: A phenomenological approach was applied to how the images of beautiful place were set by FGI group meeting, and how such factors affect beautiful place's perception from the user's point of view. When looking at comprehensive ranking of image factors in recognition of beautiful landscapes, factors corresponding to forest landscapes appear at the top rank. In determining factors for its recognition, shared space with natural elements such as water, trees, flowers, etc. has been analyzed to have the biggest influence. Among factors corresponding to urban landscape, 'streets and pedestrian paths' is of medium importance and are recognized for it is artificial structure coexisting with natural elements shared with humans. The image corresponding to 'city area' and 'architecture' was analyzed to have insignificant influence on beautiful places' image recognition for artificial element was prioritized.

건설현장 안전 지적 사항 분석 (Vocabulary Analysis of Safety Warnings in Construction Site)

  • 강경수;류한국
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2019년도 추계 학술논문 발표대회
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    • pp.40-41
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    • 2019
  • The purpose of this study is to analyze the vocabulary related to safety accidents based on the reports recorded on the violation of safety rules at the construction sites. We used Word2Vec and Topic Model as natural language processing techniques to analyze the safety accidents presented in the reports of the large enterprise. The words that appeared based on the occupational accident types such as the fall, falling objects, and others were derived and visualized. We derive the frequency and similarity of the words and topics of the accident that occur at the construction site. In future studies, we will be able to proceed with the generation of texts from pictures based on images and this reports.

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