• 한국정보통신학회논문지
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• 제25권12호
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• pp.1777-1783
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• 2021

대단위 신재생 에너지 발전단지의 효율적인 유지관리를 위해 드론의 활용이 점차 증가하고 있다. 오래전부터 태양광 패널을 드론으로 촬영하여 패널의 유실 및 오염 등을 관리하고 있다. 본 논문에서는 열화상카메라를 장착한 드론을 이용하여 획득된 태양광패널 이미지에서 아크, 단선, 크랙 등의 고장 유무를 판별하기 위해 시멘틱세그멘테이션 기법을 이용한 분류모델을 제안한다. 또한 적은 데이터셋으로도 강인한 분류 성능을 보이는 U-Net의 튜닝을 통해 효율적인 분류모델을 구현하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권5호
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• pp.1373-1387
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• 2012

Contextual advertising is an important revenue source for major service providers on the Web. Ads classification is one of main tasks in contextual advertising, and it is used to retrieve semantically relevant ads with respect to the content of web pages. However, it is difficult for traditional text classification methods to achieve satisfactory performance in ads classification due to scarce term features in ads. In this paper, we propose a novel ads classification method that handles the lack of term features for classifying ads with short text. The proposed method utilizes a vocabulary expansion technique using semantic associations among terms learned from large-scale search query logs. The evaluation results show that our methodology achieves 4.0% ~ 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.34-46
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• 2023

A growing number of large scale knowledge graphs raises several issues how knowledge graph data can be organized, discovered, and integrated efficiently. We present a novel semantic-based mashup platform for contents convergence which consists of acquisition, RDF storage, ontology learning, and mashup subsystems. This platform servers a basis for developing other more sophisticated applications required in the area of knowledge big data. Moreover, this paper proposes an entity matching method using graph convolutional network techniques as a preliminary work for automatic classification and discovery on knowledge big data. Using real DBP15K and SRPRS datasets, the performance of our method is compared with some existing entity matching methods. The experimental results show that the proposed method outperforms existing methods due to its ability to increase accuracy and reduce training time.

• 한국지능시스템학회논문지
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• 제24권2호
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• pp.166-172
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• 2014

이미지를 각각의 카테고리로 분류하는 일은 컴퓨터 비전 분야의 중요한 문제 중 하나이다. 그러나 이미지에 존재하는 가변성, 모호성, 스케일 문제 등으로 인해 매우 도전적인 문제라고 할 수 있다. 본 논문에서는 장면 이미지를 구성하는 시멘틱 속성들의 고차원의 상호작용 관계를 고려 가능한 하이퍼그래프 기반의 모델링 기법을 제시하고 이를 장면 이미지 분류에 적용한다. 각 장면 카테고리에 준최적화된 하이퍼그래프를 생성하기 위해 확률 부분공간 기법에 기반을 둔 탐색기법을 제안하고, 이들 부분 공간 내에 속한 시멘틱 속성들의 발현량을 축약하기 위한 우도비 기반의 선형 변환 기법을 제안한다. 제안한 기법의 우수성을 검증하기 위한 실험을 통하여 제시한 기법을 통해 생성된 특징 벡터의 분별력이 기존의 기법들에서 사용된 특징 벡터들의 분별력보다 우수함을 보인다. 또한 제안한 기법을 장면 분류 데이터에 적용한 결과 기존의 기법들과 비교하여 경쟁력 있는 분류 성능을 보인다. 제안 한 기법은 이미지 분류에서 일반적으로 사용 되는 기법인 BoW+SPM 모델과 비교하여 3~4%이상의 성능 향상을 보였다.

• 대한원격탐사학회지
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• 제38권4호
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• pp.395-409
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• 2022

The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

• 한국측량학회지
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• 제38권1호
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• pp.23-33
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• 2020

최근 UAV (Unmanned Aerial Vehicle)를 이용하여 고해상도 영상을 편리하게 취득할 수 있게 되면서 저비용으로 소규모 지역의 관측 및 공간정보 제작이 가능하게 되었다. 특히, 농업환경 모니터링을 위하여 작물생산 지역의 피복지도 생성에 대한 연구가 활발히 진행되고 있으며, 랜덤 포레스트와 SVM (Support Vector Machine) 및 CNN(Convolutional Neural Network) 을 적용하여 분류 성능을 비교한 결과 영상분류에서 딥러닝 적용에 대하여 활용도가 높은 것으로 나타났다. 특히, 위성영상을 이용한 피복분류는 위성영상 데이터 셋과 선행 파라메터를 사용하여 피복분류의 정확도와 시간에 대한 장점을 가지고 있다. 하지만, 무인항공기 영상은 위성영상과 공간해상도와 같은 특성이 달라 이를 적용하기에는 어려움이 있다. 이러한 문제점을 해결하기 위하여 위성영상 데이터 셋이 아닌 UAV를 이용한 데이터 셋과 국내의 소규모 복합 피복이 존재하는 농경지 분석에 활용이 가능한 딥러닝 알고리즘 적용 연구를 수행하였다. 본 연구에서는 최신 딥러닝의 의미론적 영상분류인 DeepLab V3+, FC-DenseNet (Fully Convolutional DenseNets), FRRN-B (Full-Resolution Residual Networks) 를 UAV 데이터 셋에 적용하여 영상분류를 수행하였다. 분류 결과 DeepLab V3+와 FC-DenseNet의 적용 결과가 기존 감독분류보다 높은 전체 정확도 97%, Kappa 계수 0.92로 소규모 지역의 UAV 영상을 활용한 피복분류의 적용가능성을 보여주었다.

• 가정과삶의질연구
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• 제11권1호
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• pp.159-175
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• 1993

The purpose of this study was to find out the psychological distance through semantic app-roach perceived by adolescent child in the subtypes of 'Extrem Family' dysfunctional families by classification of Olson and his associates ' Circrumplex Model. The subjects of this research were 1072 abolescents living in Seoul. Korea The survey methods were questionnaires including FACES II and The Psychological Distance Scale. Data were analyzed by means of the statistics of frequency percentage arithematic mean standard devia-tion crosstabs and one way-anova. The major findings are as follows: 1) The levels of family cohesion family adaptibility and the psychologival distances with father mother and siblings perceived by adolescent were high. 2) The most of subject's families belonged to 'Balanced Family' in the types of family system ' Extreme Family' type showed the lowest frequency and the main subtypes of it that had the highest frequency were 'Enmeshed Chaotic Family' ' Disengaged Rigid Family' 3) While adolescents of 'Enmeshed Chaotic Family' perceived most closely with other family members. those of 'Disengated Rigid Family' most distantly totally and in evaluation potency and activity three subfactors in psychological distance. 4) There were differences of unit points in subfactors of psychological distances with other family members perceived by adolescents according to the types of family system. While the points of 'Enmeshed Chaotic Family' were the highest those of 'Disengaged Rigid Family' were the lowest. 5) While 'Enmeshed Chaotic Family' were located most closely 'Disengaged Rigid Family' were located most distantly in the mutual distances and direct distances among family concepts on semantic space.

• 한국환경복원기술학회지
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• 제10권1호
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• pp.23-35
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• 2007

Nowadays, as a result of increasing income and spare time, the social demands for better living environment become more increasing. Above all, landscape improvement, the essential part of physical environment, will be a more important subject in urban planning. In these circumstances, classification of urban scenic quality is required for urban landscape development programs. The major purpose of this study is to suggest a technical method of designing urban scenic quality map for urban district area based on the scenery management system of the USDA forest service and literature studies. As a conclusion of this study, four steps are desirable for the technical method for designing a scenic quality map of urban districts areas : 1) Define a landscape unit on the map, 2) Take a photograph of these landscape unit on site, 3) Evaluate the landscape unit by semantic differential scale with landscape adjectives, and 4) Draw the scenic quality map, investigate the landscape characteristics and suggest the landscape scenic development plans.

• 한국의류학회지
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• 제19권6호
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• pp.984-994
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• 1995

The dimensional structure of impression formed of a female figure in specific attire was identified and significant influence of skirt length and suit color on impression formed of figures in suits were researched in the part I of this study. In part ll, the effect of identical elements of apparel design on impression formation of a female figure in dress and pants- blouse were studied. The experimental matirals consisted of two sets of stimuli and 7 point semantic differential response scale developed in part 1. Each set of stimuli was composed of 20 drawings representing female figures in each attire. Three independent variables, which were the length of bottom, color of dress or pants and collar type of blouse, were manipulated in each stimulus. The experiment was arranged by 3 factorial design, and the data were analyzed by 3-way ANOVA and by Multiple Classification Analysis. To summarize, in impression formation of figure in dress, the most dominant design element was identified as bottom length and the second most dominant one was color of dress. In contrast, in perception of figure in pants-blouse, the most important design element was color of pants and secondly important one was bottom length. The collar type of top didn't have critical effect on impression formation of figures in both type of attire.

• 농촌계획
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• 제14권3호
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• pp.53-61
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• 2008

This study has intended to elicit the definition of rural landscape, to classify rural landscape type, and to develop the evaluation indicators of rural landscape, meeting the definition through delphi expert survey method. The survey was performed five times for 80 days by 20 experts. The delphi expert survey asked experts as follows: 1) to fill out open-ended questions regarding the definition of rural landscape, and classification of rural landscape types, and evaluation indicators; 2) to provide their own feasibility evaluation regarding the results of the previous answer; and 3) to reevaluate the feasibility of the definition, types, and indicators. Based on the survey results, this study has found the appropriate definition of rural landscape like the comprehensive complex of physical (objective) and nonphysical (subjective) factors characterizing natural and/or artificial scenary of rural village itself Also, this study has developed the evaluation indicators of rural landscape in accordance with space types and landscape units classified. The developed indicators included areal ratio, the degree of green naturality, the building coverage ratio for physical landscape field, and skyline, landscape adjectives, color landscape, semantic scale.