• Title/Summary/Keyword: hierarchical conference

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Hierarchical active shape model-based video object tracking using wavelet transform (웨이블릿을 이용한 계층적 능동형태모델 기반 비디오 추적기술)

  • ;Vivek Maik
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.161-164
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    • 2003
  • This paper proposes a hierarchical approach to active shape model using wavelet transform. The proposed algorithm allows us to use both global shape characteristics and finer details for model deformation. The statistical properties of the wavelet transform of a deformable model are analyzed by principal component analysis and used as priors in the contour's deformation.

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Color Image Segmentation Using Anisotropic Diffusion and Agglomerative Hierarchical Clustering (비등방형 확산과 계층적 클러스터링을 이용한 칼라 영상분할)

  • 김대희;안충현;호요성
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.377-380
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    • 2003
  • A new color image segmentation scheme is presented in this paper. The proposed algorithm consists of image simplification, region labeling and color clustering. The vector-valued diffusion process is performed in the perceptually uniform LUV color space. We present a discrete 3-D diffusion model for easy implementation. The statistical characteristics of each labeled region are employed to estimate the number of total clusters and agglomerative hierarchical clustering is performed with the estimated number of clusters. Since the proposed clustering algorithm counts each region as a unit, it does not generate oversegmentation along region boundaries.

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Unification of neural network with a hierarchical pattern recognition

  • Park, Chang-Mock;Wang, Gi-Nam
    • Proceedings of the ESK Conference
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    • 1996.10a
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    • pp.197-205
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    • 1996
  • Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

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Design Considerations for Hierarchical Web Caching Scheme Using iSCSI (iSCSI를 사용한 계층적 웹 캐슁 스킴의 설계)

  • 임효택
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.161-164
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    • 2003
  • The sharing of caches among Web proxies is an important technique to reduce Web Traffic and alleviate network bottlenecks. Additionally, due to emerging network technologies cooperative Web caching among proxies shows great promise to become an effective approach for reducing Web document access latencies. Nevertheless it is not widely deployed due to the overhead of existing protocols such as ICP. We propose iSCSI-based hierarchical web caching scheme which provides more improved performance than existing web caching scheme.

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Prediction of Time Series Using Hierarchical Mixtures of Experts Through an Annealing (어닐링에 의한 Hierarchical Mixtures of Experts를 이용한 시계열 예측)

  • 유정수;이원돈
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.360-362
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    • 1998
  • In the original mixtures of experts framework, the parameters of the network are determined by gradient descent, which is naturally slow. In [2], the Expectation-Maximization(EM) algorithm is used instead, to obtain the network parameters, resulting in substantially reduced training times. This paper presents the new EM algorithm for prediction. We show that an Efficient training algorithm may be derived for the HME network. To verify the utility of the algorithm we look at specific examples in time series prediction. The application of the new EM algorithm to time series prediction has been quiet successful.

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Performance Evaluation of the JPEG DCT-based Progressive and Hierarchical Codings for Medical Image Communication

  • Ahn, C.B.;Lee, J.S.
    • Proceedings of the KOSOMBE Conference
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    • v.1991 no.11
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    • pp.48-53
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    • 1991
  • The discrete cosine transform (DCT)-based progressive and hierarchical coding schemes developed by the International Standardization Organization (ISO) Joint Photographic Experts Groups (JPEG) are implemented and evaluated for the application of medical image communication. For a series of head sections of magnetic resonance images, a compression ratio of about 10 is obtained by the algorithm without noticeable image degradation.

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COMPUTATIONAL MODELING OF KANSEI PROCESSES FOR HUMAN-CENTERED INFORMATION SYSTEMS

  • Kato, Toshikazu
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2002.05a
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    • pp.3-8
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    • 2002
  • This paper introduces the basic concept of computational modeling of perception processes for multimedia data. Such processes are modeled as hierarchical inter- and intra- relationships amongst information in physical, physiological, psychological and cognitive layers in perception. Based on our framework, this paper gives the algorithms for content-based retrieval for multimedia database systems.

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An Analysis of the Hierarchical Agglomerative Clustering based on various Compound Noun Indexing Method (복합명사 분리 색인 방법이 문서 클러스터링에 미치는 영향 분석)

  • 양명석;최성필
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.697-699
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    • 2002
  • 본 논문에서는 복합명사에 대한 색인 방법을 다각적으로 적용하여 계층적 결함 문서 클러스터링 시스템의 결과를 분석하고자 한다. 우선 한글 색인 엔진과 HAC(Hierarchical Agglumerative Clustering) 엔진에 대해서 설명하고 한글 색인엔진에서 제공되는 세가지 복합명사 분석 모드에 대해서 설명한다. 또한 구현된 클러스터링 엔진의 특징과 속도 향상을 위한 기법 등을 설명한다. 실험에서는 다양한 요소를 가지고 클러스터링된 문서 집합에 대한 분석 결과를 보인다. 실험 결과에 대한 분석에서 복합명사에 대한 색인 방법이 문서 클러스터링의 결과에 직접적인 영향을 준다는 것을 보여준다.

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The Hierarchical Structure of Semantic Property (명사의 의미소성의 계층구조)

  • Yoon, K.J.;Park, C.K.;Lee, J.K.
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.616-619
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    • 1988
  • This paper deals with a semantic properties of Korea noun for semantic process in machine translation. The procedure is carried out as follow; 1) 17,000 words of Korean nouns are collected. 2) Semantic category is classifed into 39 markers. 3) We slow the redundancy of semantic properties and improve the efficiency of dictionary by marking the hierarchical concept structure.

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Balancing and Position Control of an Circular Inverted Pendulum System Using Self-Learning Fuzzy Controller (자기학습 퍼지제어기를 이용한 원형 역진자 시스템의 안정화 및 위치 제어)

  • 김용태;변증남
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.172-175
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    • 1996
  • In the paper is proposed a hierarchical self-learning fuzzy controller for balancing and position control of an circular inverted pendulum system. To stabilize the pendulum at a specified position, the hierarchical fuzzy controller consists of a supervisory controller, a self-learning fuzzy controller, and a forced disturbance generator. Simulation example shows the effectiveness of the proposed method.

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