• Title/Summary/Keyword: Classification

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

  • Lee, Kyoo-Seock;Lee, In-Soo;Jeon, Seong-Woo
    • Proceedings of the KSRS Conference
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    • 1999.11a
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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
    • Korean Journal of Remote Sensing
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    • v.28 no.6
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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.

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

  • Kim Myung-Ok
    • Journal of the Korean Society for Library and Information Science
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    • v.25
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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
    • Journal of Intelligence and Information Systems
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    • v.1 no.1
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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
    • Korean Journal of Remote Sensing
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    • v.18 no.3
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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
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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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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    • v.38 no.1
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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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    • v.55 no.5
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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.

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

  • Song, Mi-Young;Kim, Hong-Jun;Choi, Hwan-Soo
    • Korean Journal of Oriental Medicine
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    • v.11 no.2
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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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On the Use of Modified Adaptive Nearest Neighbors for Classification (수정된 적응 최근접 방법을 활용한 판별분류방법에 대한 연구)

  • Maeng, Jin-Woo;Bang, Sung-Wan;Jhun, Myoung-Shic
    • The Korean Journal of Applied Statistics
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    • v.23 no.6
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    • pp.1093-1102
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    • 2010
  • Even though the k-Nearest Neighbors Classification(KNNC) is one of the popular non-parametric classification methods, it does not consider the local features and class information for each observation. In order to overcome such limitations, several methods have been developed such as Adaptive Nearest Neighbors Classification(ANNC) and Modified k-Nearest Neighbors Classification(MKNNC). In this paper, we propose the Modified Adaptive Nearest Neighbors Classification(MANNC) that employs the advantages of both the ANNC and MKNNC. Through a real data analysis and a simulation study, we show that the proposed MANNC outperforms other methods in terms of classification accuracy.