• 제목/요약/키워드: Classification

검색결과 22,065건 처리시간 0.045초

The Comparison of Visual Interpretation & Digital Classification of SPOT Satellite Image

  • Lee, Kyoo-Seock;Lee, In-Soo;Jeon, Seong-Woo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.433-438
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    • 1999
  • The land use type of Korea is high-density. So, the image classification using coarse resolution satellite image may not provide land cover classification results as good as expected. The purpose of this paper is to compare the result of visual interpretation with that of digital image classification of 20 m resolution SPOT satellite image at Kwangju-eup, Kyunggi-do, Korea. Classes are forest, cultivated field, pasture, water and residential area, which are clearly discriminated in visual interpretation. Maximum likelihood classifier was used for digital image classification. Accuracy assessment was done by comparing each classification result with ground truth data obtained from field checking. The classification result from the visual interpretation presented an total accuracy 9.23 percent higher than that of the digital image classification. This proves the importance of visual interpretation for the area with high density land use like the study site in Korea.

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Classification of Fused SAR/EO Images Using Transformation of Fusion Classification Class Label

  • Ye, Chul-Soo
    • 대한원격탐사학회지
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    • 제28권6호
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    • pp.671-682
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    • 2012
  • Strong backscattering features from high-resolution Synthetic Aperture Rader (SAR) image provide useful information to analyze earth surface characteristics such as man-made objects in urban areas. The SAR image has, however, some limitations on description of detail information in urban areas compared to optical images. In this paper, we propose a new classification method using a fused SAR and Electro-Optical (EO) image, which provides more informative classification result than that of a single-sensor SAR image classification. The experimental results showed that the proposed method achieved successful results in combination of the SAR image classification and EO image characteristics.

서양의 자료분류법의 발달과정 - 고대에서 해리스까지 - (The History of Library Classification before Dewey in Western library)

  • 김명옥
    • 한국문헌정보학회지
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    • 제25권
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    • pp.185-213
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    • 1993
  • This study is on the history of classification in Western library from ancient to Harris(1870), before Dewey. It looks into the classification systems of librarians, bibliographers, booksellers and libraries of that time. One of the earliest was the classification of the clay tablets in the Assyrian library of Assurbanipal. But the earliest recorded system in the papyrus is that which Callimachus(B.C. 310-240) devised for the library at Alexandria. In the medival, the monastry libraries used many classifications. but their libraries were very small. Gesner, Naude, Brunet, Jefferson, Edwards, Harris etc. tried to make a good classification for bibliographies and libraries. Especially Brunet made the scheme based on the French system, and it used on bibliographical classification and shelf classification in the many libraries. In 1859, Edwards made the classification scheme for the public library in the Great Britain. In 1870, Harris made the famous inverted Baconian classification and it strongly influenced the Dewey Decimal Classification.

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Blackboard Scheduler Control Knowledge for Recursive Heuristic Classification

  • Park, Young-Tack
    • 지능정보연구
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    • 제1권1호
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    • pp.61-72
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    • 1995
  • Dynamic and explicit ordering of strategies is a key process in modeling knowledge-level problem-solving behavior. This paper addressed the important problem of howl to make the scheduler more knowledge-intensive in a way that facilitates the acquisition, integration, and maintenance of the scheduler control knowledge. The solution a, pp.oach described in this paper involved formulating the scheduler task as a heuristic classification problem, and then implementing it as a classification expert system. By doing this, the wide spectrum of known methods of acquiring, refining, and maintaining the knowledge of a classification expert system are a, pp.icable to the scheduler control knowledge. One important innovation of this research is that of recursive heuristic classification : this paper demonstrates that it is possible to formulate and solve a key subcomponent of heuristic classification as heuristic classification problem. Another key innovation is the creation of a method of dynamic heuristic classification : the classification alternatives that are selected among are dynamically generated in real-time and then evidence is gathered for and aginst these alternatives. In contrast, the normal model of heuristic classification is that of structured selection between a set of preenumerated fixed alternatives.

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Comparison of Visual Interpretation and Image Classification of Satellite Data

  • Lee, In-Soo;Shin, Dong-Hoon;Ahn, Seung-Mahn;Lee, Kyoo-Seock;Jeon, Seong-Woo
    • 대한원격탐사학회지
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    • 제18권3호
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    • pp.163-169
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    • 2002
  • The land uses of Korean peninsula are very complicated and high-density. Therefore, the image classification using coarse resolution satellite images may not provide good results for the land cover classification. The purpose of this paper is to compare the classification accuracy of visual interpretation with that of digital image classification of satellite remote sensing data such as 20m SPOT and 30m TM. In this study, hybrid classification was used. Classification accuracy was assessed by comparing each classification result with reference data obtained from KOMPSAT-1 EOC imagery, air photos, and field surveys.

Supervised Classification Using Training Parameters and Prior Probability Generated from VITD - The Case of QuickBird Multispectral Imagery

  • Eo, Yang-Dam;Lee, Gyeong-Wook;Park, Doo-Youl;Park, Wang-Yong;Lee, Chang-No
    • 대한원격탐사학회지
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    • 제24권5호
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    • pp.517-524
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    • 2008
  • In order to classify an satellite imagery into geospatial features of interest, the supervised classification needs to be trained to distinguish these features through training sampling. However, even though an imagery is classified, different results of classification could be generated according to operator's experience and expertise in training process. Users who practically exploit an classification result to their applications need the research accomplishment for the consistent result as well as the accuracy improvement. The experiment includes the classification results for training process used VITD polygons as a prior probability and training parameter, instead of manual sampling. As results, classification accuracy using VITD polygons as prior probabilities shows the highest results in several methods. The training using unsupervised classification with VITD have produced similar classification results as manual training and/or with prior probability.

Classification of endometriosis

  • Lee, Soo-Young;Koo, Yu-Jin;Lee, Dae-Hyung
    • Journal of Yeungnam Medical Science
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    • 제38권1호
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    • pp.10-18
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    • 2021
  • Endometriosis is a chronic disease associated with pelvic pain and infertility. Several classification systems for the severity of endometriosis have been proposed. Of these, the revised American Society for Reproductive Medicine classification is the most well-known. The ENZIAN classification was developed to classify deep infiltrating endometriosis and focused on the retroperitoneal structures. The endometriosis fertility index was developed to predict the fertility outcomes in patients who underwent surgery for endometriosis. Finally, the American Association of Gynecological Laparoscopists classification is currently being developed, for which 30 endometriosis experts are analyzing and researching data by assigning scores to categories considered important; however, it has not yet been fully validated and published. Currently, none of the classification systems are considered the gold standard. In this article, we review the classification systems, identify their pros and cons, and discuss what improvements need to be made to each system in the future.

An integrated risk-informed safety classification for unique research reactors

  • Jacek Kalowski;Karol Kowal
    • Nuclear Engineering and Technology
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    • 제55권5호
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    • pp.1814-1820
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    • 2023
  • Safety classification of systems, structures, and components (SSC) is an essential activity for nuclear reactor design and operation. The current regulatory trend is to require risk-informed safety classification that considers first, the severity, but also the frequency of SSC failures. While safety classification for nuclear power plants is covered in many regulatory and scientific publications, research reactors received less attention. Research reactors are typically of lower power but, at the same time, are less standardized i.e., have more variability in the design, operational modes, and operating conditions. This makes them more challenging when considering safety classification. This work presents the Integrated Risk-Informed Safety Classification (IRISC) procedure which is a novel extension of the IAEA recommended process with dedicated probabilistic treatment of research reactor designs. The article provides the details of probabilistic analysis performed within safety classification process to a degree that is often missing in most literature on the topic. The article presents insight from the implementation of the procedure in the safety classification for the MARIA Research Reactor operated by the National Center for Nuclear Research in Poland.

국제특허분류를 중심으로 한 한의학 분야의 특허정보 분석 연구 (A Study on the Analysis of Patent information in the Korean Medicine -Focused on International Patent Classification-)

  • 송미영;김홍준;최환수
    • 한국한의학연구원논문집
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    • 제11권2호
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    • pp.67-96
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    • 2005
  • This Study focused on IPC (International Patent Classification) for TKM (Traditional Korea Medicine) Paper. The results processed for 9,000 TKM paper by using 8th in IPC Classification. The name of Herbal Medicine assigned to IPC Classification, we assigned to two part for main-Classification(A61K) and sub-Classification (A61P). The results obtained about 77% for A61K and about 96% for A61K36 among them. And also analysed about 23% for sub-Classification(A61P) additionally. Main-Classification is distributed A61K > A61H37 > A61B5 > A61N > A61M1. Detailed Main-Classification for A61K is distributed A61K36 > A61K35 > A61K33 among Main-Classification. TKM Paper mainly analysed A61K36 and A61H37 in Main-Classification. According to the results. 'The Korean Journal of Herbology' has high-valued for Utilization as a Non Patent Document. we should constructed Database system for protection of intellectual property rights. And after We will registered minimum documentation of PCT.

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수정된 적응 최근접 방법을 활용한 판별분류방법에 대한 연구 (On the Use of Modified Adaptive Nearest Neighbors for Classification)

  • 맹진우;방성완;전명식
    • 응용통계연구
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    • 제23권6호
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    • pp.1093-1102
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    • 2010
  • 비모수적 판별분류방법인 k-Nearest Neighbors Classification(KNNC) 방법은 널리 사용되고 있지만 고정된 이웃의 개수를 사용하며 또한 집단변수의 정보를 활용하지 않음으로서 자료의 국소적 특징을 반영하지 못하는 단점이 있다. Adaptive Nearest Neighbors Classification(ANNC) 방법과 Modified k-Nearest Neighbors Classification(MKNNC) 방법은 각각 이러한 단점들을 보완하기 위해 제안된 방법이다. 본 연구에서는 ANNC 방법과 MKNNC 방법의 장점을 결합한 Modified Adaptive Nearest Neighbors Classification(MANNC) 방법을 제안하였다. 나아가, 제안된 방법의 활용 가능성을 살펴보고자 실제자료에 대한 분석과 모의실험을 통해 기존의 방법들과 비교하였다.