• Title/Summary/Keyword: LDA 혼합 모형

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Face Recognition using LDA Mixture Model (LDA 혼합 모형을 이용한 얼굴 인식)

  • Kim Hyun-Chul;Kim Daijin;Bang Sung-Yang
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.789-794
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    • 2005
  • LDA (Linear Discriminant Analysis) provides the projection that discriminates the data well, and shows a very good performance for face recognition. However, since LDA provides only one transformation matrix over whole data, it is not sufficient to discriminate the complex data consisting of many classes like honan faces. To overcome this weakness, we propose a new face recognition method, called LDA mixture model, that the set of alf classes are partitioned into several clusters and we get a transformation matrix for each cluster. This detailed representation will improve the classification performance greatly. In the simulation of face recognition, LDA mixture model outperforms PCA, LDA, and PCA mixture model in terms of classification performance.

Extensions of LDA by PCA Mixture Model and Class-wise Features (PCA 혼합 모형과 클래스 기반 특징에 의한 LDA의 확장)

  • Kim Hyun-Chul;Kim Daijin;Bang Sung-Yang
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.781-788
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    • 2005
  • LDA (Linear Discriminant Analysis) is a data discrimination technique that seeks transformation to maximize the ratio of the between-class scatter and the within-class scatter While it has been successfully applied to several applications, it has two limitations, both concerning the underfitting problem. First, it fails to discriminate data with complex distributions since all data in each class are assumed to be distributed in the Gaussian manner; and second, it can lose class-wise information, since it produces only one transformation over the entire range of classes. We propose three extensions of LDA to overcome the above problems. The first extension overcomes the first problem by modeling the within-class scatter using a PCA mixture model that can represent more complex distribution. The second extension overcomes the second problem by taking different transformation for each class in order to provide class-wise features. The third extension combines these two modifications by representing each class in terms of the PCA mixture model and taking different transformation for each mixture component. It is shown that all our proposed extensions of LDA outperform LDA concerning classification errors for handwritten digit recognition and alphabet recognition.

Prosodic Break Index Estimation using LDA and Tri-tone Model (LDA와 tri-tone 모델을 이용한 운율경계강도 예측)

  • 강평수;엄기완;김진영
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.7
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    • pp.17-22
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    • 1999
  • In this paper we propose a new mixed method of LDA and tri-tone model to predict Korean prosodic break indices(PBI) for a given utterance. PBI can be used as an important cue of syntactic discontinuity in continuous speech recognition(CSR). The model consists of three steps. At the first step, PBI was predicted with the information of syllable and pause duration through the linear discriminant analysis (LDA) method. At the second step, syllable tone information was used to estimate PBI. In this step we used vector quantization (VQ) for coding the syllable tones and PBI is estimated by tri-tone model. In the last step, two PBI predictors were integrated by a weight factor. The proposed method was tested on 200 literal style spoken sentences. The experimental results showed 72% accuracy.

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Establishment of ITS Policy Issues Investigation Method in the Road Section applied Textmining (텍스트마이닝을 활용한 도로분야 ITS 정책이슈 탐색기법 정립)

  • Oh, Chang-Seok;Lee, Yong-taeck;Ko, Minsu
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.6
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    • pp.10-23
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    • 2016
  • With requiring circumspections using big data, this study attempts to develop and apply the search method for audit issues relating to the ITS policy or program. For the foregoing, the auditing process of the board of audit and inspection was converged with the theoretical frame of boundary analysis proposed by William Dunn as an analysis tool for audit issues. Moreover, we apply the text mining technique in order to computerize the analysis tool, which is similar to the boundary analysis in the concept of approaching meta-problems. For the text mining analysis, specific model we applied the antisymmetry-symmetry compound lexeme-based LDA model based on the Latent Dirichlet Allocation(LDA) methodologies proposed by David Blei. The several prime issues were founded through a case analysis as follows: lack of collection of traffic information by the urban traffic information system, which is operated by the National Police Agency, the overlapping problems between the Ministry of Land, Infrastructure and Transport and the Advanced Traffic Management System and fabrication of the mileage on digital tachograph.