• 제목/요약/키워드: Weak Threshold

검색결과 86건 처리시간 0.023초

Stagewise Weak Orthogonal Matching Pursuit Algorithm Based on Adaptive Weak Threshold and Arithmetic Mean

  • Zhao, Liquan;Ma, Ke
    • Journal of Information Processing Systems
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    • 제16권6호
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    • pp.1343-1358
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    • 2020
  • In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

판별 함수를 이용한 문턱치 선정에 의한 약분류기 개선 (Improving Weak Classifiers by Using Discriminant Function in Selecting Threshold Values)

  • 샴 아디카리;유현중;김형석
    • 한국콘텐츠학회논문지
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    • 제10권12호
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    • pp.84-90
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    • 2010
  • Viola와 Jones가 사용한 Haar-like 특징 기반 약분류기의 분별력을 개선하기 위하여, 2차 판별식에 기반한 판정 경계(decision boundary) 결정 방법을 제안한다. Viola와 Jones가 부스팅된 약분류기 앙상블을 사용해서 강분류기를 만들 때 사용한 단일 판정 경계 기반 약분류기는 특징 공간을 지나치게 단순하게 해석한 산물이어서 대부분의 경우 최적이 아니며, 객체 클래스와 배경 클래스 간을 효율적으로 분별하기에 흔히 너무 약하다. 이 논문에서 제안하는 2차 판별식 분석에 기반한 방법은 객체 클래스와 배경 클래스 사이에 다중 판정 경계를 사용하는 약분류기를 만들어준다. 1000개의 positive 샘플과 3000개의 negative 샘플을 훈련에 사용하고, 500개의 positive와 500개의 negative를 테스트에 사용한 차량 검출 실험을 통해서, 기존의 단일 문턱치 기반 약분류기 방식에 비해, 제안 기법이 더 적은 수의 분류기를 사용하면서도 더 우수한 분류 성능을 제공하는 것을 확인하였다.

혼합 약한 분류기를 이용한 AdaBoost 알고리즘의 성능 개선 방법 (A Method to Improve the Performance of Adaboost Algorithm by Using Mixed Weak Classifier)

  • 김정현;등죽;김진영;강동중
    • 제어로봇시스템학회논문지
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    • 제15권5호
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    • pp.457-464
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    • 2009
  • The weak classifier of AdaBoost algorithm is a central classification element that uses a single criterion separating positive and negative learning candidates. Finding the best criterion to separate two feature distributions influences learning capacity of the algorithm. A common way to classify the distributions is to use the mean value of the features. However, positive and negative distributions of Haar-like feature as an image descriptor are hard to classify by a single threshold. The poor classification ability of the single threshold also increases the number of boosting operations, and finally results in a poor classifier. This paper proposes a weak classifier that uses multiple criterions by adding a probabilistic criterion of the positive candidate distribution with the conventional mean classifier: the positive distribution has low variation and the values are closer to the mean while the negative distribution has large variation and values are widely spread. The difference in the variance for the positive and negative distributions is used as an additional criterion. In the learning procedure, we use a new classifier that provides a better classifier between them by selective switching between the mean and standard deviation. We call this new type of combined classifier the "Mixed Weak Classifier". The proposed weak classifier is more robust than the mean classifier alone and decreases the number of boosting operations to be converged.

측두하악장애환자에서 다양한 종류의 정량적 통각검사들의 연관성에 관한 연구 (Associations Among Different Types of Quantitative Pain Measures in TMD Patients)

  • 박지운;김용우;정진우
    • Journal of Oral Medicine and Pain
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    • 제32권4호
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    • pp.413-419
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    • 2007
  • 다양한 종류의 정량적 통각검사들의 연관성을 알아보기 위하여 56 명의 측두하악장애 환자를 대상으로 측두근, 교근, 측두하악관절 부위, 그리고 경골근의 냉통각역치 (Cold Pain Threshold, CPT), 열통각역치 (Heat Pain Threshold, HPT), 열통증인내역치 (Heat Pain Tolerance Threshold, PTT), 압력통각역치 (Pressure Pain Threshold, PPT)를 측정하였으며, 각기 다른 통각 역치 간의 상관관계와 측정 부위 별 통각 역치 간의 상관 관계를 분석하였다. CPT, HPT, PTT를 포함한 온도통각역치의 성별간 차이는 나타나지 않았다. 그러나 PPT는 여성이 남성에 비하여 모든 부위에서 유의하게 낮은 역치를 나타내었다. CPT, HPT, PTT를 포함한 세 가지의 온도통각역치들은 모든 측정 부위에서 약정도에서 강정도 (mild to high)의 상관관계를 나타내었다 (r= 0.324-0.754, p<0.05). PPT 값은 각각의 온도통각역치와 통계적으로 유의한 상관관계를 나타내지 않았다. 모든 측정 부위의 통각역치값들은 서로간에 약정도에서 강정도 (mild to high)의 상관관계를 나타내었다 (r= 0.284-0.878, p<0.05). 측두하악장애 환자의 온도통각역치와 열통각인내역치 사이에는 유의한 상관관계가 존재하나 온도통각역치와 압력통각역치 간에는 상관관계가 나타나지 않는 것이 관찰되었으며, 각기 다른 부위에서 측정된 통각역치 간에는 비교적 높은 상관관계가 나타났다.

An Improvement of AdaBoost using Boundary Classifier

  • 이원주;천민규;현창호;박민용
    • 한국지능시스템학회논문지
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    • 제23권2호
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    • pp.166-171
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    • 2013
  • The method proposed in this paper can improve the performance of the Boosting algorithm in machine learning. The proposed Boundary AdaBoost algorithm can make up for the weak points of Normal binary classifier using threshold boundary concepts. The new proposed boundary can be located near the threshold of the binary classifier. The proposed algorithm improves classification in areas where Normal binary classifier is weak. Thus, the optimal boundary final classifier can decrease error rates classified with more reasonable features. Finally, this paper derives the new algorithm's optimal solution, and it demonstrates how classifier accuracy can be improved using the proposed Boundary AdaBoost in a simulation experiment of pedestrian detection using 10-fold cross validation.

Infrastructure-Growth Link and the Threshold Effects of Sub-Indices of Institutions

  • OGBARO, Eyitayo Oyewunmi;OLADEJI, Sunday Idowu
    • Asian Journal of Business Environment
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    • 제11권1호
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    • pp.17-25
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    • 2021
  • Purpose: This study extends previous empirical work on the threshold effects of institutions on the relationship between infrastructure and economic growth. It does so by using three sub-indices of institutions as the threshold variable in place of aggregate index. This is with a view to determining the roles of the sub-indices in the nexus between infrastructure and economic growth. Research design, data and methodology: The analysis is based on a dynamic panel threshold regression model using a panel data set comprising 41 countries in Sub-Saharan Africa over the sample period of 1996-2015. Data are obtained from Ogbaro (2019). Results: The study finds that infrastructure exerts significant positive effects on economic growth below and above the threshold values of the three sub-indices, with higher effects above the threshold values. Results also show that on average, the Sub-Saharan African countries are not able to satisfy any of the threshold conditions, which accounts for their poor growth experience. Conclusion: The study concludes that countries with weak institutions do not benefit maximally from infrastructure development policies. The paper, therefore, recommends that countries in Sub-Saharan Africa need to focus on improving their institutional patterns if they are to reap the optimum benefits from their infrastructure development efforts.

LOD방법을 이용한 미소신호 검출의 최적 임계치 결정 (Determination of Optimum Threshold Value for Weak Signal Detection by LOD Method)

  • 이재환;신승호;진용옥
    • 한국통신학회논문지
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    • 제10권3호
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    • pp.123-129
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    • 1985
  • 본 연구는 100kHz의 대역폭에서 SNR이 0dB 정도인 미소신호의 존재유무를 판단하기 위한 임계치 결정방법에 대하여 기술한 것이다. 검출방법은 니만-피어슨등의 전통적인 방법에 비해서 미소신호에 적합한 LOD방법을 적용한 것이다. 검출의 대상신호는 데이터전송이나 모르스부호 전소에 사용되는 OOK변조신호이고, 잡음은 전송로에서 일반적으로 존재하는 라프라시안형의 비가우시안형을 대상으로 하였다. 실험결과, 오판확률을 임의의 값으로 고정시키고, 한 점의 임계를 취한 경우에서의 검출확률과 두 점의 구간임계점을 상호, 비교한 결과 후자의 검출방법이 현저히 향상됨을 확인하였다.

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광섬유링센서에서 유도되는 브루앤파의 혼돈 및 비안정화 현상 (Chaotic and Instability Effects in Brillouin-Active Fiber-Ring Sensor)

  • Kim, Yong K.;Kim, Jin-Su
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제53권6호
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    • pp.337-341
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    • 2004
  • In this paper the effect of chaos induced instability in Brillouin-active fiber-ring sensor is described. The inherent optical feedback by the backscattered Stokes wave in optical fiber leads to instabilities in the form of optical chaos. The paradigm of optical chaos in fiber serves as a test for fundamental study of chaos and its suppression and exploitation in practical application in communication and sensing. At weak power, the nature of the Brillouin instability can occur at before threshold. At strong power, the temporal evolution above threshold is periodic and at higher intensity can become chaotic. The threshold for the Brillouin instability in fiber-ring sensor is much lower than the threshold of the normal Brillouin instability process.

THE MODIFIED BRIGHTNESS TEMPERATURE DIFFERENCE FOR AEROSOL DETECTION

  • Kim, Jae-Hwan;Ha, Jong-Sung;Lee, Hyun-Jin
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.794-796
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    • 2006
  • This study investigated the Brightness Temperature Difference threshold as criterion between aerosols and clouds in conjunction with radiative transfer model. Surface temperature is caused by a significant error over 50% in the BTD threshold. In addition, The BTD threshold contains the uncertainties about 20% due to the surface emissivity and 8% due to the satellite zenith angle. Therefore, we have composed the Look-up table for BTD between 11㎛and 12㎛ according to satellite zenith angle, surface temperature, and surface emissivity. The modified BTD show the enhanced signal, especially over bright surface such as desert in China. However, a weak aerosol signal over Ocean remains in the modified BTD.

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특징분포를 고려한 AdaBoost 약분류기의 성능 개선방법 (A Method to Improve the Performance of Weak Classifier in AdaBoost by Considering Features Distribution)

  • 이경주;최형일;김계영
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2012년도 제45차 동계학술발표논문집 20권1호
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    • pp.209-211
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    • 2012
  • 본 논문에서는 AdaBoost 알고리즘에서 약분류기(Weak Classifier)의 성능을 개선하기 위한 임계값 설정 방법을 제안한다. 일반적으로 약분류기에 사용되는 임계값은 특징들의 평균값을 많이 사용하지만 이는 특징들의 분포가 고려되지 않았기 때문에 분별력이 많이 떨어진다. 그러므로 각 특징들의 분포를 고려한 약분류기의 임계값 설정방법을 제안한다. 이는 얼굴에 대한 간단한 학습 및 테스트를 통하여 기존 방법에 비하여 더 나은 성능을 보임을 입증한다.

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