• Title/Summary/Keyword: pattern recognition

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A Study on the Fingerprint Recognition Method using Neural Networks (신경회로망을 이용한 지문인식방법에 관한 연구)

  • Lee, Ju-Sang;Lee, Jae-Hyeon;Kang, Seong-In;Kim, IL;Lee, Sang-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.287-290
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    • 2000
  • In this paper we have presented approach to automatic the direction feature vectors detection, which detects the ridge line directly in gray scale images. In spite of a greater conceptual complexity, we have shown that our technique has less computational complexity than the complexity of the techniques which require binarization and thinning. Afterwards a various direction feature vectors is changed four direction feature vectors. In this paper used matching method is four direction feature vectors based matching. This four direction feature vectors consist feature patterns in fingerprint images. This feature patterns were used for identification of individuals inputed multilayer Neural Networks(NN) which has capability of excellent pattern identification.

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Unification of Kohonen Neural network with the Branch-and-Bound Algorithm in Pattern Clustering

  • Park, Chang-Mok;Wang, Gi-Nam
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.134-138
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    • 1998
  • Unification of Kohone SOM(Self-Organizing Maps) neural network with the branch-and-bound algorithm is presented for clustering large set of patterns. The branch-and-bound search technique is employed for designing coarse neural network learning paradaim. Those unification can be use for clustering or calssfication of large patterns. For classfication purposes further usefulness is possible, since only two clusters exists in the SOM neural network of each nodes. The result of experiments show the fast learning time, the fast recognition time and the compactness of clustering.

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An Elliptic Approach to Learning Discriminabts

  • KARBOU, Fatiha;KARBOU, Fatima;KARBOU, M.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.143-147
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    • 1998
  • It sis wisely stated that the most valuable knowledge that a person can acquire is the knowledge of how to learn. The human's learning is characterized by the ability to extract relationships between the different characters of a given situation . The ellipse is a first approach of comparison. We assimilate each character to a half axis of the ellipse and the result is a geometrical figure that varies according to values of the two characters. Thus, we take into account the two characters as an alone entity.

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An EIIiptic Approach to Learning Discriminants

  • Karbou, Fatiha;Karbou, Fatima;Karbou, M.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.153-157
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    • 1998
  • It is wisely stated that the most valuable knowledge that a person cam acquire is the knowledge of how to learn. The human's learning is characterized by the ability to extract relationships between the different characters of a given situation. The ellipse is a first approach of comparison. We assimilate each character to a half axis of the ellipse and the result is a geometrical figure that varies according to values of the two characters. Thus, we take into account the two characters as an alone entity.

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A Neural Fuzzy Learning Algorithm Using Neuron Structure

  • Yang, Hwang-Kyu;Kim, Kwang-Baek;Seo, Chang-Jin;Cha, Eui-Young
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.395-398
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    • 1998
  • In this paper, a method for the improvement of learning speed and convergence rate was proposed applied it to physiological neural structure with the advantages of artificial neural networks and fuzzy theory to physiological neuron structure, To compare the proposed method with conventional the single layer perception algorithm, we applied these algorithms bit parity problem and pattern recognition containing noise. The simulation result indicated that our learning algorithm reduces the possibility of local minima more than the conventional single layer perception does. Furthermore we show that our learning algorithm guarantees the convergence.

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Genetic Outlier Detection for a Robust Support Vector Machine

  • Lee, Heesung;Kim, Euntai
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.2
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    • pp.96-101
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    • 2015
  • Support vector machine (SVM) has a strong theoretical foundation and also achieved excellent empirical success. It has been widely used in a variety of pattern recognition applications. Unfortunately, SVM also has the drawback that it is sensitive to outliers and its performance is degraded by their presence. In this paper, a new outlier detection method based on genetic algorithm (GA) is proposed for a robust SVM. The proposed method parallels the GA-based feature selection method and removes the outliers that would be considered as support vectors by the previous soft margin SVM. The proposed algorithm is applied to various data sets in the UCI repository to demonstrate its performance.

Innate immune response to oral bacteria and the immune evasive characteristics of periodontal pathogens

  • Ji, Suk;Choi, Youngnim
    • Journal of Periodontal and Implant Science
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    • v.43 no.1
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    • pp.3-11
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    • 2013
  • Periodontitis is a chronic inflammation of periodontal tissue caused by subgingival plaque-associated bacteria. Periodontitis has long been understood to be the result of an excessive host response to plaque bacteria. In addition, periodontal pathogens have been regarded as the causative agents that induce a hyperinflammatory response from the host. In this brief review, host-microbe interaction of nonperiodontopathic versus periodontopathic bacteria with innate immune components encountered in the gingival sulcus will be described. In particular, we will describe the susceptibility of these microbes to antimicrobial peptides (AMPs) and phagocytosis by neutrophils, the induction of tissue-destructive mediators from neutrophils, the induction of AMPs and interleukin (IL)-8 from gingival epithelial cells, and the pattern recognition receptors that mediate the regulation of AMPs and IL-8 in gingival epithelial cells. This review indicates that true periodontal pathogens are poor activators/suppressors of a host immune response, and they evade host defense mechanisms.

Predicting Unknown Composition of a Mixture Using Independent Component Analysis

  • Lee, Hye-Seon;Park, Hae-Sang;Jun, Chi-Hyuck
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.127-134
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    • 2005
  • A suitable representation for the conceptual simplicity of the data in statistics and signal processing is essential for a subsequent analysis such as prediction, pattern recognition, and spatial analysis. Independent component analysis (ICA) is a statistical method for transforming an observed high-dimensional multivariate data into statistically independent components. ICA has been applied increasingly in wide fields of spectrum application since ICA is able to extract unknown components of a mixture from spectra. We focus on application of ICA for separating independent sources and predicting each composition using extracted components. The theory of ICA is introduced and an application to a metal surface spectra data will be described, where subsequent analysis using non-negative least square method is performed to predict composition ratio of each sample. Furthermore, some simulation experiments are performed to demonstrate the performance of the proposed approach.

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Effects of pH on Purification of GFPuv/Cytochrome c-552 Fusion Protein

  • Lee, Sang-On;Hong, Eul-Jae;Choe, Jeong-U;Hong, Eok-Gi
    • 한국생물공학회:학술대회논문집
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    • 2003.04a
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    • pp.539-542
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    • 2003
  • Fusion gene of GFPuv and Cytochrome c-552 was inserted into the pTrcHis B vector and transferred to E. coli. A fusion protein of GFPuv and Cytochrome c-552 was expressed in BL21. This fusion protein was composed of a His-tag for purification using an immobilized metal affinity chromatography(IMAC). IMAC constitutes a rather facile means of unravelling the principles of recognition and, in particular, of identifying the counterligands on the protein surface, which interact with the ligated and immobilized metal ions. Histidine when present on the surface of a protein molecule under a favorable solvent condition, may serve as electron donors in coordination with the immobilized chelates of some transition metal ions$(Ni^{2+})$.

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Design of an Intelligent Integrated Control System Using Neural Network (뉴럴 네트워크를 이용한 지능형 통합 제어 시스템 설계)

  • 정동연;김경년;이정호;김원일;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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    • pp.381-386
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    • 2002
  • In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

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