• Title/Summary/Keyword: 기술 분류

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Comparative Research of Image Classification and Image Segmentation Methods for Mapping Rural Roads Using a High-resolution Satellite Image (고해상도 위성영상을 이용한 농촌 도로 매핑을 위한 영상 분류 및 영상 분할 방법 비교에 관한 연구)

  • CHOUNG, Yun-Jae;GU, Bon-Yup
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.3
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    • pp.73-82
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    • 2021
  • Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

Syllables-based Named Entity Extraction and Automatic Corpus Construction using Bidirectional Dynamic LST (Bidirectional Dynamic LSTM 을 이용한 음절 단위 개체명 추출 및 자동화된 말뭉치 구축)

  • Oh, Sungsik;Lim, Changdae;Ahn, Keeho;Park, Weijin
    • Annual Conference on Human and Language Technology
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    • 2017.10a
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    • pp.317-320
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    • 2017
  • 개체명 인식은 자연어 문장에서 장소, 제작물, 사람 등 분류를 통한 의미 부여가 가능한 단어를 파악하는 기술로서 의미 분석을 위한 핵심 기술이다. 현재 많은 개체명 분석 관련 연구들은 형태소 분석 결과에 의존적인 형태를 갖고 있어서, 형태소 분석 결과의 정확성이 개체명 분석 결과의 성능에 영향을 미치고 있다. 본 연구에서는 형태소 분석 과정을 거치지 않는 음절 기반의 개체명 분석 기술을 제안하여 형태소 분석의 정확도가 낮은 통신어, 신조어 분석 성능을 향상하였다. 또한, 자동화된 방법으로 음절 단위 개체명 말뭉치 및 개체명 사전을 구축하는 프로세스를 정의하여 개체명 분석의 정확도 향상 및 인지 범주의 확대를 도모하였다. 본 연구에서 제안한 개체명 인식 기술은 한국어 개체명 표준에 기반한 129가지의 개체명 분류가 가능하며, 이는 자연어 처리 기술이 필요한 산업계에서 상용화하는데 큰 기여를 할 것으로 판단된다.

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Automatic Music-Story Video Generation Using Music Files and Photos in Automobile Multimedia System (자동차 멀티미디어 시스템에서의 사진과 음악을 이용한 음악스토리 비디오 자동생성 기술)

  • Kim, Hyoung-Gook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.5
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    • pp.80-86
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    • 2010
  • This paper presents automated music story video generation technique as one of entertainment features that is equipped in multimedia system of the vehicle. The automated music story video generation is a system that automatically creates stories to accompany musics with photos stored in user's mobile phone by connecting user's mobile phone with multimedia systems in vehicles. Users watch the generated music story video at the same time. while they hear the music according to mood. The performance of the automated music story video generation is measured by accuracies of music classification, photo classification, and text-keyword extraction, and results of user's MOS-test.

인체 삽입용 표면처리 임플란트의 인허가 절차

  • Kim, Yeong-Hyeon;Kim, Jun-Gyu;Nam, Hyeon-Sik;Kim, Dong-Rim;Park, So-Jin;Park, Eun-Yeong
    • Proceedings of the Korean Institute of Surface Engineering Conference
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    • 2018.06a
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    • pp.22-22
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    • 2018
  • 의료기기는 사용목적과 사용 시 인체에 미치는 잠재적 위해성의 정도에 따라 4개의 등급으로 분류하며, 두 가지 이상의 등급에 해당되는 제품의 경우에는 가장 높은 등급으로 분류하게 된다. 의료기기 품목허가를 위해서는 기술문서를 작성하여야 하며, 이를 위해서는 기술문서 심사를 신청하는 절차를 이해하여야 한다. 의료기기 기술문서란 의료기기의 성능과 안전성 등 품질에 관한 자료로서 해당 품목의 원자재, 구조, 사용목적, 사용방법, 작용원리, 사용 시 주의사항, 시험규격 등이 포함되는 문서를 말하며, '의료기기 허가 신청서'와 '첨부자료(임상시험자료 포함)'로 구성되어 있다. 의료기기 품목허가 시 제출되는 기술문서를 통하여 해당 의료기기의 안전성 및 성능이 충분히 입증되어야 하며, 인체 삽입되는 표면처리 임플란트를 포함한 인체 접촉 의료기기의 안전성의 경우 '의료기기의 생물학적 안전에 관한 공통 기준규격'에 따라 평가 후 제조 수입품목 허가를 진행해야 한다. 또한 성능의 경우는 해당 규격 또는 자사의 기준 및 시험방법에 따른 성능에 관한 자료, 물리 화학적 특성에 관한 자료를 통하여 평가되어야 하며, 기허가 인증된 제품에 한 번도 사용되지 않은 원재료 또는 적용부위 및 적용방법이 달라 안전성 및 유효성 확인이 필요한 경우 임상시험에 관한 자료가 요구될 수 있다. 본 발표에서는 이러한 인체 삽입용 표면처리 임플란트의 전반적인 인허가 절차에 대해서 안내하고자 한다.

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Design and Application of a XML Based Product Catalog (XML기반 상품 카탈로그의 설계 및 적용)

  • Ha, Sang-Ho;Kim, Gyeong-Rae
    • The KIPS Transactions:PartD
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    • v.9D no.3
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    • pp.523-530
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    • 2002
  • With an advent of XML(extensible markup language), researches on electronic commerce based on XML have been conducted by many organizations and companies. Although these researches described electronic catalogs, they are not sufficient because in the catalogs, the product information are not classified properly, and are not organized hierarchically. In this paper, we analyse and classify information that can use to describe various products. And then, we suggest the modes that can describe the various products information through the complement of existing researches, and we apply it over several products on the Web. The uses of this model supports flexibility and facility to the product offers such as internet shopping malls.

Building and Analysis of Semantic Network on S&T Multilingual Terminology (과학기술 전문용어의 다국어 의미망 생성과 분석)

  • Jeong, Do-Heon;Choi, Hee-Yoon
    • Journal of Information Management
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    • v.37 no.4
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    • pp.25-47
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    • 2006
  • A terminology system capable of providing interpretations and classification information on a multilingual science and technology(S&T) terminology is essential to establish an integrated search environment for multilingual S&T information systems. This paper aims to build a base system to manage an integrated information system for multilingual S&T terminology search. It introduces a method to build a search system for S&T terminologies internally linked through the multilingual semantic network and a search technique on the multiple linked nodes. In order to provide a foundation for further analysis researches, it also attempts to suggest a basic approach to interpret terminology clusters generated with those two search methods.

Morphological Characteristics and Principal Component Analysis of Plums (자두의 형태적 특성과 주성분 분석에 의한 품종군 분류)

  • Chung, Kyeong-Ho
    • Horticultural Science & Technology
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    • v.17 no.1
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    • pp.23-28
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    • 1999
  • To examine taxonomic relationships among 53 plums derived from Prunus cerasifera, P. domestica, and P. salicina, principal component analysis (PCA) and cluster analysis on 27 morphological characters were conducted. Of 27 characters, leaf size, leaf shape, and leaf hair were useful characters for plum identification and understanding of taxonomic relationships among them. Leaf length, petiole length, number of leaf nectaries, leaf shape, leaf base, and date of full blooming showed the clear differences between P. salicina group and P. domestica group. Results of cluster analysis using scores of the first three principal components indicated that 53 plums could be grouped into P. salicina-P. cerasifera, P. domestica, and P. spinosa phenon at 1.0 of average distance in UPGMA. Although PCA was useful for rough classification of plums, much more characters were needed for the exact classification.

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Hierarchical Automatic Classification of News Articles based on Association Rules (연관규칙을 이용한 뉴스기사의 계층적 자동분류기법)

  • Joo, Kil-Hong;Shin, Eun-Young;Lee, Joo-Il;Lee, Won-Suk
    • Journal of Korea Multimedia Society
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    • v.14 no.6
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    • pp.730-741
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    • 2011
  • With the development of the internet and computer technology, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The conventional document categorization method used only the keywords of related documents for document classification. However, this paper proposed keyword extraction method of based on association rule. This method extracts a set of related keywords which are involved in document's category and classifies representative keyword by using the classification rule proposed in this paper. In addition, this paper proposed the preprocessing method for efficient keywords creation and predicted the new document's category. We can design the classifier and measure the performance throughout the experiment to increase the profile's classification performance. When predicting the category, substituting all the classification rules one by one is the major reason to decrease the process performance in a profile. Finally, this paper suggested automatically categorizing plan which can be applied to hierarchical category architecture, extended from simple category architecture.

Suggesting a Plan of Tables of Preference for KDC4 (한국십진분류법의 우선순위표 설정에 관한 연구)

  • 배영활;오동근
    • Journal of Korean Library and Information Science Society
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    • v.33 no.2
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    • pp.167-187
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    • 2002
  • This study suggests a plan of tables of deference for Korean Decimal Classification, 4th edition, based on the study on those in Dewey Decimal Classification, 21st edition. It suggests two tables for the Auxiliary Tables, one for standard subdivisions and one for subdivisions for literature. Twenty-two tables are suggested for the Schedule of ten main classes.

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Time-Series based Dataset Selection Method for Effective Text Classification (효율적인 문헌 분류를 위한 시계열 기반 데이터 집합 선정 기법)

  • Chae, Yeonghun;Jeong, Do-Heon
    • The Journal of the Korea Contents Association
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    • v.17 no.1
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    • pp.39-49
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    • 2017
  • As the Internet technology advances, data on the web is increasing sharply. Many research study about incremental learning for classifying effectively in data increasing. Web document contains the time-series data such as published date. If we reflect time-series data to classification, it will be an effective classification. In this study, we analyze the time-series variation of the words. We propose an efficient classification through dividing the dataset based on the analysis of time-series information. For experiment, we corrected 1 million online news articles including time-series information. We divide the dataset and classify the dataset using SVM and $Na{\ddot{i}}ve$ Bayes. In each model, we show that classification performance is increasing. Through this study, we showed that reflecting time-series information can improve the classification performance.