• Title/Summary/Keyword: nearest-neighbor analysis

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Face Representation and Face Recognition using Optimized Local Ternary Patterns (OLTP)

  • Raja, G. Madasamy;Sadasivam, V.
    • Journal of Electrical Engineering and Technology
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    • v.12 no.1
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    • pp.402-410
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    • 2017
  • For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.

A Comparison Study of Classification Algorithms in Data Mining

  • Lee, Seung-Joo;Jun, Sung-Rae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.1-5
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    • 2008
  • Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

Analysis of k-Nearest Neighbor Search in High-Demensional Vector Spaces (고차원 벡터 공간에서 k-최근접 검색에 관한 분석)

  • 최승락;곽태영;신봉근;이윤준;김명호
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10b
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    • pp.191-193
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    • 1998
  • 지금까지 제시된 최근접 질의 알고리즘은다소간의 cklms 있으나 기본적으로 질의 점과 MBR간의 최소거리에 기반한 분기와 한정 기법을 이용하고 있다. 그러나 차원이 증가함에 따라 질의 구와 겹치는 노드가 급속히 증가하기 때문에 최근접 질의 알고리즘의 성능은 매우 비효율적이다. 이러한 문제를 해결하기 위해서 MBR 간의 중첩을 줄이고 MBR 내에 가급적 많은 점을 포함할 수 있는 다양한 다차원 색인 구조가 제시도 되었다. 그러나 우리의 실험에 의하면 이러한 방법이 근본적인 해결책이 되지 못함을 알 수 있다. 고차원 백터 공간 모델이 가지는 문제로써 임의의 질의 점으로부터 모든 데이터 점들까지의 거리가 차원이 올라감에 따라 유사해지는 현상 때문에 비효율적인 성능이 나옴을 본 논문에서 지적한다.

Posture Symmetry based Motion Capture System for Analysis of Lower -limbs Rehabilitation Training

  • Lee, Seok-Jun;Jung, Soon-Ki
    • Journal of Korea Multimedia Society
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    • v.14 no.12
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    • pp.1517-1527
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    • 2011
  • This paper presents a motion capture based rehabilitation training system for a lower-limb paretic patient. The system evaluates the rehabilitation status of the patient by using the bend posture of the knees and the weight balance of the body. The posture of both legs is captured with a single camera using the planar mirror. The weight distribution is obtained by the Wii Balance Board. Self-occlusion problem in the tracking of the legs is resolved by using k-nearest neighbor based clustering with body symmetry and local-linearity of the posture data. To do this, we present data normalization and its symmetric property in the normalized vector space.

Analysis of Bluetooth Indoor Localization Technologies and Experiemnt of Correlation between RSSI and Distance

  • Kim, Yang-Su;Jang, Beakcheol
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.10
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    • pp.55-62
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    • 2016
  • In this paper, we present indoor localization technologies using the bluetooth signal categorizing them into proximity based, triangulation based and fingerprinting based technologies. Then we provide localization accuracy improvement algorithms such as moving average, K-means, particle filter, and K-Nearest neighbor algorithms. We define important performance issues for indoor localization technologies and analyze recent technologies according to the performance issues. Finally we provide experimental results for correlation between RSSI and distance. We believe that this paper provide wise view and necessary information for recent localization technologies using the bluetooth signal.

Structural Arrangements and Bonding Analysis of MgB2C2

  • Kang, Dae-Bok
    • Bulletin of the Korean Chemical Society
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    • v.31 no.9
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    • pp.2565-2570
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    • 2010
  • The orthorhombic $MgB_2C_2$ structure contains well-separated parallel graphite-like $B_2C_2^{2-}$ layers which extend infinitely in two dimensions. Three possible ways to distribute B and C atoms in the hexagonal sublattice sites are adopted. Band structures for the hypothetical distribution patterns are examined to assess the electronic stability of these phases and to account for the observed arrangement by means of extended Huckel tight-binding calculations. The preferred choice is the layer with B and C alternating strictly so that B is nearest neighbor to C and vice versa. A rationale for this is given. Due to the alternation of B and C within the honeycomb layers, $MgB_2C_2$ is a band insulator, which through partial substitution of Mg with Li, is predicted to turn metallic with holes in the $\sigma$ bands at the Fermi level.

Person Recognition Using Gait and Face Features on Thermal Images (열 영상에서의 걸음걸이와 얼굴 특징을 이용한 개인 인식)

  • Kim, Sa-Mun;Lee, Dae-Jong;Lee, Ho-Hyun;Chun, Myung-Geun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.65 no.2
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    • pp.130-135
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    • 2016
  • Gait recognition has advantage of non-contact type recognition. But It has disadvantage of low recognition rate when the pedestrian silhouette is changed due to bag or coat. In this paper, we proposed new method using combination of gait energy image feature and thermal face image feature. First, we extracted a face image which has optimal focusing value using human body rate and Tenengrad algorithm. Second step, we extracted features from gait energy image and thermal face image using linear discriminant analysis. Third, calculate euclidean distance between train data and test data, and optimize weights using genetic algorithm. Finally, we compute classification using nearest neighbor classification algorithm. So the proposed method shows a better result than the conventional method.

Empirical Analysis of K-Nearest Neighbor Recommendation Engine using Vector Similarity (K-최근접 이웃 추천 엔진에서의 벡터 유사도 사용에 대한 실험적 분석)

  • 김혜재;손기락
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.103-105
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    • 2001
  • 인터넷 사용 인구의 폭증으로 인터넷 사이트가 경쟁적으로 유용한 각종 정보를 사용자들에게 제공하여 보다 많은 수의 회원을 확보하기 위해 노력하고 있지만 여러 사이트를 동시에 사용하고 있는 대부분의 인터넷 사용자들에게는 각 사이트에서 날아드는 정보를 매번 일일이 검색해야 하는 일이 여간 번거롭지 않을 뿐만 아니라 이런 무분별하고 획일적인 정보 서비스는 오히려 사용자들의 인터넷 사용을 불편하게 하며 더욱이 그 내용이 관심 밖의 것이 경우 네트워크의 효율적인 사용을 저해하는 정보공해에 지나지 않게 된다. 추천엔진은 기본으로 끊임없이 유입되는 다량의 정보 중에서 필요한 것을 추천해 주는 것이다. 이에 본 논문에서는 사용자들에게 필요한 정보만을 효율적으로 전달 해주기 위해서 먼저 개인화된 정보의 전달을 위해 사용자의취향을 파악하여 선택 가능성이 높은 항목을 예측할 수 있어야 한다. 그리고 사용자와 가까운 K 명의 사용자들을 효율적으로 검색하기 위해서 K-최근접 이웃 방식을 사용하고 인덱싱을 사용할 수 있는 세가지 벡터 유사도를 기존의 피어슨 상관계수(Pearson Correlation)와 비교하여 제안한다. 이를 통해 정보의 효율적인 제공방법, 즉 일반적인 검색으로 인한 정보의 제공이 아닌 일반 사용자들의 추천에 의해 정보를 제공하는 K-최근접 이웃 추천 엔진을 세가지 벡터 유사도를 이용해서 분석한다.

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Empirical variogram for achieving the best valid variogram

  • Mahdi, Esam;Abuzaid, Ali H.;Atta, Abdu M.A.
    • Communications for Statistical Applications and Methods
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    • v.27 no.5
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    • pp.547-568
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    • 2020
  • Modeling the statistical autocorrelations in spatial data is often achieved through the estimation of the variograms, where the selection of the appropriate valid variogram model, especially for small samples, is crucial for achieving precise spatial prediction results from kriging interpolations. To estimate such a variogram, we traditionally start by computing the empirical variogram (traditional Matheron or robust Cressie-Hawkins or kernel-based nonparametric approaches). In this article, we conduct numerical studies comparing the performance of these empirical variograms. In most situations, the nonparametric empirical variable nearest-neighbor (VNN) showed better performance than its competitors (Matheron, Cressie-Hawkins, and Nadaraya-Watson). The analysis of the spatial groundwater dataset used in this article suggests that the wave variogram model, with hole effect structure, fitted to the empirical VNN variogram is the most appropriate choice. This selected variogram is used with the ordinary kriging model to produce the predicted pollution map of the nitrate concentrations in groundwater dataset.

Empirical Analysis & Comparisons of Web Document Classification Methods (문서분류 기법을 이용한 웹 문서 분류의 실험적 비교)

  • Lee, Sang-Soon;Choi, Jung-Min;Jang, Geun;Lee, Byung-Soo
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.154-156
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    • 2002
  • 인터넷의 발전으로 우리는 많은 정보와 지식을 인터넷에서 제공받을 수 있으며 HTML, 뉴스그룹 문서, 전자메일 등의 웹 문서로 존재한다. 이러한 웹 문서들은 여러가지 목적으로 분류해야 할 필요가 있으며 이를 적용한 시스템으로는 Personal WebWatcher, InfoFinder, Webby, NewT 등이 있다. 웹 문서 분류 시스템에서는 문서분류 기법을 사용하여 웹 문서의 소속 클래스를 결정하는데 문서분류를 위한 기법 중 대표적인 알고리즘으로 나이브 베이지안(Naive Baysian), k-NN(k-Nearest Neighbor), TFIDF(Term Frequency Inverse Document Frequency)방법을 이용한다. 본 논문에서는 웹 문서를 대상으로 이러한 문서분류 알고리즘 각각의 성능을 비교 및 평가하고자 한다.

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