• 제목/요약/키워드: local linear method

검색결과 420건 처리시간 0.029초

MAP 추정 알고리즘에 의한 레이더 영상에서 도로검출 (Detection of Road Features Using MAP Estimation Algorithm In Radar Images)

  • 김순백;이수흠;김두영
    • 융합신호처리학회 학술대회논문집
    • /
    • 한국신호처리시스템학회 2003년도 하계학술대회 논문집
    • /
    • pp.62-65
    • /
    • 2003
  • We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing information from these detectors. The second is global step, we identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

  • PDF

SAR 영상에서 MRF기반 도로 검출 (Detection of Road Based on MRF in SAR Images)

  • 김순백;이상학;김두영
    • 융합신호처리학회 학술대회논문집
    • /
    • 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
    • /
    • pp.121-124
    • /
    • 2000
  • We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing Information from these detectors. The second is hybrid step, we Identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

  • PDF

신경 회로망을 이용한 비선형 계통의 제어 (Nonlinear System Control using Neural Networks)

  • 이기상;박태건;임재형;이정동
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 1994년도 추계학술대회 논문집 학회본부
    • /
    • pp.356-358
    • /
    • 1994
  • In this paper, to alleviate the effect of approximation error and discontinuous variation of the controller parameters, the variable structure control scheme using neural networks is presented. In the proposed method, the variable structure control rules for each local linear models are designed to reject the effect of linearization error caused by linearization of the nonlinear system. And neural network infer approximate controller gains from combination of local linear control gains. The proposed control methods can be used to control nonlinear systems and it has robust characteristic against system parameter variations and external disturbances.

  • PDF

MRF를 이용한 레이더 영상에서 도로검출 (Detection of Road Features Using MRF in Radar Images)

  • 김순백;정래형;김두영
    • 융합신호처리학회 학술대회논문집
    • /
    • 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
    • /
    • pp.221-224
    • /
    • 2000
  • We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing information from these detectors. The second is global step, we identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

  • PDF

Regression discontinuity for survival data

  • Youngjoo Cho
    • Communications for Statistical Applications and Methods
    • /
    • 제31권1호
    • /
    • pp.155-178
    • /
    • 2024
  • Regression discontinuity (RD) design is one of the most widely used methods in causal inference for estimation of treatment effect when the treatment is created by a cutpoint from the covariate of interest. There has been little attention to RD design, although it provides a very useful tool for analysis of treatment effect for censored data. In this paper, we define the causal effect for survival function in RD design when the treatment is assigned deterministically by the covariate of interest. We propose estimators of this causal effect for survival data by using transformation, which leads unbiased estimator of the survival function with local linear regression. Simulation studies show the validity of our approach. We also illustrate our proposed method using the prostate, lung, colorectal and ovarian (PLCO) dataset.

강성응축기법을 이용한 국부 비선형 정적 해석 (Local Nonlinear Static Analysis via Static Condensation)

  • 신한섭;오민한;부승환
    • 해양환경안전학회지
    • /
    • 제27권1호
    • /
    • pp.193-200
    • /
    • 2021
  • 본 연구에서는 국부 비선형 정적 해석을 효율적으로 수행하기 위하여 강성응축(Static condensation)을 활용한 해석기법을 제시하였다. 강성응축기법은 자유도 기반의 유한요소 모델 축소기법이며, 해석 모델을 관심 대상(Target) 부분과 응축되어 생략될(Omitted) 부분으로 구분한다. 본 연구에서는, 관심 대상 부분에는 비선형 영역, 생략될 부분에는 선형 영역으로 지정하였고, 선형 영역에 대응되는 강성 행렬 및 하중 벡터를 비선형 영역, 즉 관심 대상 부분으로 모두 응축하였다. 모델 응축 후에는 비선형 영역에 대한 강성 행렬 및 하중 벡터만으로 이루어진 축소 모델을 구성하였으며, 이 축소 모델만을 뉴턴-랩슨 반복(Newton-Raphson iteration)을 통해 갱신하여 효율적으로 비선형 해석을 수행하였다. 끝으로, 제안된 기법을 다양한 수치 예제에 적용하여 해석기법의 효율성과 신뢰성을 제시하였다.

Edge Adaptive Hierarchical Interpolation for Lossless and Progressive Image Transmission

  • Biadgie, Yenewondim;Wee, Young-Chul;Choi, Jung-Ju
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제5권11호
    • /
    • pp.2068-2086
    • /
    • 2011
  • Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

Joint Access Point Selection and Local Discriminant Embedding for Energy Efficient and Accurate Wi-Fi Positioning

  • Deng, Zhi-An;Xu, Yu-Bin;Ma, Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제6권3호
    • /
    • pp.794-814
    • /
    • 2012
  • We propose a novel method for improving Wi-Fi positioning accuracy while reducing the energy consumption of mobile devices. Our method presents three contributions. First, we jointly and intelligently select the optimal subset of access points for positioning via maximum mutual information criterion. Second, we further propose local discriminant embedding algorithm for nonlinear discriminative feature extraction, a process that cannot be effectively handled by existing linear techniques. Third, to reduce complexity and make input signal space more compact, we incorporate clustering analysis to localize the positioning model. Experiments in realistic environments demonstrate that the proposed method can lower energy consumption while achieving higher accuracy compared with previous methods. The improvement can be attributed to the capability of our method to extract the most discriminative features for positioning as well as require smaller computation cost and shorter sensing time.

Action Recognition with deep network features and dimension reduction

  • Li, Lijun;Dai, Shuling
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제13권2호
    • /
    • pp.832-854
    • /
    • 2019
  • Action recognition has been studied in computer vision field for years. We present an effective approach to recognize actions using a dimension reduction method, which is applied as a crucial step to reduce the dimensionality of feature descriptors after extracting features. We propose to use sparse matrix and randomized kd-tree to modify it and then propose modified Local Fisher Discriminant Analysis (mLFDA) method which greatly reduces the required memory and accelerate the standard Local Fisher Discriminant Analysis. For feature encoding, we propose a useful encoding method called mix encoding which combines Fisher vector encoding and locality-constrained linear coding to get the final video representations. In order to add more meaningful features to the process of action recognition, the convolutional neural network is utilized and combined with mix encoding to produce the deep network feature. Experimental results show that our algorithm is a competitive method on KTH dataset, HMDB51 dataset and UCF101 dataset when combining all these methods.

지방정부규모와 지역경제성장 간 비선형관계 분석: AMG 추정법을 이용한 Armey Curve 검증 (An Analysis of Non-linear Relationship between Local Government Size and Regional Economic Growth: Armey Curve Verification Using AMG Estimation Method)

  • 김소연;류수열
    • 한국경제지리학회지
    • /
    • 제25권4호
    • /
    • pp.629-640
    • /
    • 2022
  • 본 연구는 2002-2020년 기간의 지역 데이터를 사용하여 지방정부규모와 지역경제성장 간의 관계를 분석하였다. 지방정부지출을 사회개발비와 경제개발비로 나누어 GRDP 성장률과 역U자 형태의 Armey 곡선의 관계가 존재하는지 검증하고, 최적의 지방정부지출의 수준을 살펴보고자 하였다. 특히, 추정방법에 있어서 패널자료에 존재하는 횡단면 의존성과 지역별 이질성을 고려한 AMG 추정법을 활용하였다. 분석 결과, 총지방재정지출 및 사회개발비의 규모와 지역경제성장 간에 역U자형 관계가 나타났고, 경제개발비와 지역경제성장 간에는 역U자형 관계가 존재하지 않는 것으로 나타났다. 총지방재정지출 비중이 GRDP 대비 7.63%일 때, 사회개발비 비중은 3.45%일 때 지역경제성장률을 극대화할 수 있는 최적의 지출규모인 것으로 나타났다. 지방정부는 이러한 점을 고려하여 공공지출 정책의 실효성을 높여야 한다.