• 제목/요약/키워드: statistical processing

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Statistical Image Processing using Java on the Web

  • Lim, Dong Hoon;Park, Eun Hee
    • Communications for Statistical Applications and Methods
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    • 제9권2호
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    • pp.355-366
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    • 2002
  • The web is one of the most plentiful sources of images. The web has an immediate need for image processing technology in Java. This paper provides a practical introduction to statistical image processing using Java on the web. The paper describes how images are represented in Java and deals with four image processing operations based on basic statistical methods: point processing, spatial filtering, edge detection and image segmentation.

Developing the Quality Assessment Indicators for the National Processing Statistics of Korea

  • Kim, Soo-Taek;Jeong, Ki-Ho;Kim, Seol-Hee
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.649-665
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    • 2007
  • The improvement of quality is a continuous process and one of the main objectives of the Statistical Strategy launched by the Korea National Statistical Office (KNSO) is the enhancement of the quality of Korea national statistics. In this paper, we define the processing statistic, classify the Korea national processing statistics, and develop the quality indicators and check list for assessing the national processing statistics of Korea. During its development, the indicators has been discussed with the processing statistic managers of the KNSO and the checklist tested in a pilot study covering a variety of processing statistic areas.

문맥의존 철자오류 후보 생성을 위한 통계적 언어모형 개선 (Improved Statistical Language Model for Context-sensitive Spelling Error Candidates)

  • 이정훈;김민호;권혁철
    • 한국멀티미디어학회논문지
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    • 제20권2호
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    • pp.371-381
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    • 2017
  • The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

Development of Apple Color Grading System by Statistical Color Image Processing

  • Lim, Dong-Hoon
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.325-332
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    • 2003
  • This study was to develop a system for grading apples by their color using statistical image processing. T-test was used to detect edges in apple images and the chain code method was used for contour coding. The histogram and mean gray level of each RGB channel in a ring-shaped region was used to compare apple colors to reference apple color.

통계전문가시스템을 위한 통계처리과정의 공학적 접근 연구 (Engineering approach of Statistics Processing for the Statistical Expert System)

  • 차홍준
    • 응용통계연구
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    • 제3권1호
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    • pp.1-9
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    • 1990
  • 본 연구는 통계처리과정을 공학적인 접근으로한 인공지능화를 시도하려는 개념화에 있는데, 이는 전산학에서의 소프트웨어공학과 같이 통계지식공학으로 확대 적용하고, 더불어 그 관계를 일반화 해보려는 것이다. 그러므로 방법적인 도출은 통계전문가시스템 설계를 하는데 불변성으로 명확하게 나타내려는 것이 아니라 발전적으로 요구되는 편의를 위해서 유연한 대처로 했으며, 이를 위한 지식의 표현 방안을 확실히 구성했다. 따라서 이를 확대 적용할 수 있도록 공학적 처리 모형을 개념화 하여서 이러한 문제의 공학적인 접근 방안을 제안했다.

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On-Line Analytical Processing and Research Problems for Statisticians

  • Ahn, JeongYong;Han, Kyung Soo
    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.457-463
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    • 2000
  • Recently, statistical analysis tools have been changed to the applications on the World Wide Web that access data stored in databases. On-line analytical processing(OLAP) is a class of technologies that give users statistical information with multidimensional views of data in databases. In this paper, we introduce the concept and requisites of OLAP system, and we propose some research issues.

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다중 통계기법을 이용한 고속 하프변환 (Fast Hough Transform Using Multi-statistical Methods)

  • 조보호;정성환
    • 한국멀티미디어학회논문지
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    • 제19권10호
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    • pp.1747-1758
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    • 2016
  • In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

비간섭 전력 부하 감시용 고차 적률 특징을 갖는 전력 신호 인식 (Power Signal Recognition with High Order Moment Features for Non-Intrusive Load Monitoring)

  • 민황기;안태훈;이승원;이성로;송익호
    • 한국통신학회논문지
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    • 제39C권7호
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    • pp.608-614
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    • 2014
  • 이 논문에서는 비간섭 전력 부하 감시에 알맞은 패턴 인식 시스템을 다룬다. 전력 신호의 고차 적률 정보를 써서 전기기구를 효과적으로 분별하여 인식할 수 있는 새로운 특징 추출 방법을 제안한다. 동작 특성이 비슷한 두 전기기구를 제안한 고차 적률 특징과 커널 판별 분석을 쓰는 패턴 인식 시스템이 효과적으로 분별하여 인식할 수 있다는 것을 모의실험으로 보인다.

MEMS 기술로 제작된 가스 센서 어레이를 이용한 유해가스 분류를 위한 간단한 통계적 패턴인식방법의 구현 (Implementation of simple statistical pattern recognition methods for harmful gases classification using gas sensor array fabricated by MEMS technology)

  • 변형기;신정숙;이호준;이원배
    • 센서학회지
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    • 제17권6호
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    • pp.406-413
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    • 2008
  • We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

A Novel Statistical Feature Selection Approach for Text Categorization

  • Fattah, Mohamed Abdel
    • Journal of Information Processing Systems
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    • 제13권5호
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    • pp.1397-1409
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    • 2017
  • For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods.