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다중 패턴 분류를 위한 Import Vector Voting 모델 (Import Vector Voting Model for Multi-pattern Classification)

  • 최준혁;김대수;임기욱
    • 한국지능시스템학회논문지
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    • 제13권6호
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    • pp.655-660
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    • 2003
  • 일반적으로 Support Vector Machine은 이진 분류 모형에 있어 우수한 성능을 보이지만 모델의 한계로 인하여 다중 패턴의 분류 문제에는 쉽게 적용하기가 어렵다. 본 논문에서는 이진 분류를 포함한 다중 레이블을 갖는 데이터의 정확한 패턴 분류를 위하여 Zhu가 제안한 Import Vector Machine에 커널 Bagging 전략을 적용하여 분류의 정확성을 향상시키기 위한 Import Vector Voting 모형을 제안한다. 이러한 Import Vector Voting 모형은 다수의 커널함수를 적용한 결과 중에서 가장 성능이 우수한 커널함수를 이용하여 최종 분류를 수행하기 위한 voting 전략으로 사용한다. 본 논문에서 제안하는 Import Vector Voting 모형은 이진 분류를 포함한 3개 이상의 다중 패턴 데이터에 대한 분류 문제에 있어 매우 정확한 분류 성능을 보임을 실험을 통해 입증한다.

GENERALIZED VECTOR-VALUED VARIATIONAL INEQUALITIES AND FUZZY EXTENSIONS

  • Lee, Byung-Soo;Lee, Gue-Myung;Kim, Do-Sang
    • 대한수학회지
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    • 제33권3호
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    • pp.609-624
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    • 1996
  • Recently, Giannessi [9] firstly introduced the vector-valued variational inequalities in a real Euclidean space. Later Chen et al. [5] intensively discussed vector-valued variational inequalities and vector-valued quasi variationl inequalities in Banach spaces. They [4-8] proved some existence theorems for the solutions of vector-valued variational inequalities and vector-valued quasi-variational inequalities. Lee et al. [14] established the existence theorem for the solutions of vector-valued variational inequalities for multifunctions in reflexive Banach spaces.

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A METHOD FOR ADJUSTING ADAPTIVELY THE WEIGHT OF FEATURE IN MULTI-DIMENSIONAL FEATURE VECTOR MATCHING

  • Ye, Chul-Soo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.772-775
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    • 2006
  • Muilti-dimensional feature vector matching algorithm uses multiple features such as intensity, gradient, variance, first or second derivative of a pixel to find correspondence pixels in stereo images. In this paper, we proposed a new method for adjusting automatically the weight of feature in multi-dimensional feature vector matching considering sharpeness of a pixel in feature vector distance curve. The sharpeness consists of minimum and maximum vector distances of a small window mask. In the experiment we used IKONOS satellite stereo imagery and obtained accurate matching results comparable to the manual weight-adjusting method.

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Efficacy of Gene Transfer of Recombinant Baculovirus Vector

  • Sa, Young-Hee;Hong, Seong-Karp
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2013년도 춘계학술대회
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    • pp.1006-1008
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    • 2013
  • A novel recombinant baculovirus vector system containing coding genes for polyhedron promoter, vesicular stomatitis virus G (VSVG), polyA, cytomegalovirus (CMV) promoter, enhanced green fluorescent protein (EGFP), and protein transduction domain (PTD) was constructed. We applied this recombinant baculovirus vector into cells and murine tissues and compared efficacy of gene transfer and expression of this recombinant baculovirus vector system with control vector system. From this result, we confirmed that this novel recombinant baculovirus vector system was very effective than control vector system.

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First Principle을 결합한 최소제곱 Support Vector Machine의 예측 능력 (Prediction Performance of Hybrid Least Square Support Vector Machine with First Principle Knowledge)

  • 김병주;심주용;황창하;김일곤
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제30권7_8호
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    • pp.744-751
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    • 2003
  • 본 논문에서는 최근 뛰어난 예측력으로 각광받는 최소제곱 Support Vector Machine(Least Square Support Vector Machine: LS-SVM)과 First Principle(FP)을 결합한 하이브리드 최소제곱ㆍSupport Vector Machine 모델, HLS-SVM(Hybrid Least Square-Super Vector Machine)을 제안한다. 제안한 모델인 하이브리드 최소제곱 Support Vector Machine을 기존의 방법인 하이브리드 신경망(Hybrid Neural Network:HNN), 비선형 칼만필터와 하이브리드 신경망을 결합한 HNN-EKF (Hybrid Neural Network with Extended Kalman Filter) 모델과 비교해 보았다. HLS-SVM 모델은 학습 및 validation 과정에서는 HNN-EKF와 근사한 성능을 보였고, HNN 보다는 우수한 결과를 보였고, 일반화 성능에서는 HNN-EKF에 비해 3배, HNN보다 100배정도 우수한 결과를 보였다.

움직임 벡터 분할을 이용한 움직임 보상 성능 개선 (Performance Improvement of Motion Compensation using Motion Vector Segmentation)

  • 채종길;곽성일;황찬식
    • 전자공학회논문지B
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    • 제32B권3호
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    • pp.77-88
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    • 1995
  • It is assumed in the block matching algorithm(BMA) that all the pels in a block have a same motion vector. Then, the motion vector of a block in the BMA is matched to only one or none of the objects in the worst case if objects in a block have different motion vectors. This is apparent in the motion estimation using the fast BMA which has the effect of reducing the computation time and hardware complexity, compared to the full search BMA. Although the motion vector in the motion estimation using small block size is accurate, the increased number of bits is required to represent motion vectors. In this paper, new motion vector segmentation with less additional information and hardware complexity than the conventional method is proposed. In the proposed method, a motion vector is derived from the block for motion vector segmentation and another motion vector is extracted from four neighboring blocks to consiture a motion vector pair. For the accurate motion vector of each subblock, the motion vector is assigned to each subblock by mean squared error measure. And the overlapped motion compensation using window is also applied to reduce displaced frame difference.

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Vector Bundles on Curves with Many "spread" Sections

  • Ballico, E.
    • Kyungpook Mathematical Journal
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    • 제45권2호
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    • pp.167-169
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    • 2005
  • Here we introduce and study vector bundles, E, on a smooth projective curve X having many "spread" sections and for which $E^{*}\;{\otimes}{\omega}X$ has many "spread" sections. We show that no such bundle exists on X if the gonality of X is too low.

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SADDLE POINTS OF VECTOR-vALUED FUNCTIONS IN TOPOLOGICAL VECTOR SPACES

  • Kim, In-Sook
    • 대한수학회지
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    • 제37권5호
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    • pp.849-856
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    • 2000
  • We give a new saddle point theorem for vector-valued functions on an admissible compact convex set in a topological vector space under weak condition that is the semicontinuity of two function scalarization and acyclicty of the involved sets. As application, we obtain the minimax theorem.

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