• 대한원격탐사학회지
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• 제26권3호
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• The Korean Journal of Ecology
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• 제16권1호
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• pp.1-15
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• 1993

Ordination and classification techiques were used to analyze the forest communities and to examine the integration problem of community-to-ecological species group in mt. moak provincial park of korea. phytosociological classiication based on floristic composition produced seven commuities of zelkova serrata, carpinus densiflora. These seven communities were well discriminated in the two-dimensional analyses of soil moisture, soil organic matter content and temperature(elevation), eciprocally, and in three-dimensional space of the three environmental factors also. They corresponded to seven ecological groups derived from the distribution pattern analysis of species populations in this mountain.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.517-521
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• 2008

Hand motion classification problem is considered as basis for sign or gesture recognition. We promote optical flow as main feature extracted from images sequences to simultaneously segment the motion's area by its magnitude and characterize the motion' s directions by its orientation. We manage the flow orientation histogram as motion descriptor. A motion is encoded by concatenating the flow orientation histogram from several frames. We utilize simple histogram matching to classify the motion sequences. Attempted experiments show the feasibility of our method for hand motion localization and classification.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.627-635
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• 2003

In this short communication we discuss the bias problem of C4.5 in split variable selection and suggest a method to reduce the variable selection bias among categorical predictor variables. A penalty proportional to the number of categories is applied to the splitting criterion gain of C4.5. The results of empirical comparisons show that the proposed modification of C4.5 reduces the size of classification trees.

• 대한수학회지
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• 제54권5호
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• pp.1411-1440
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• 2017

We study free actions of finite groups on 3-dimensional nil-manifolds with the first homology ${\mathbb{Z}}^2{\oplus}{\mathbb{Z}}_p$. By the works of Bieberbach and Waldhausen, this classification problem is reduced to classifying all normal nilpotent subgroups of almost Bieberbach groups of finite index, up to affine conjugacy.

• Journal of the Korean Statistical Society
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• 제28권2호
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• pp.183-193
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• 1999

In the problem of estimating estimable functions in classification linear models, we propose a method of obtaining least squares estimators of estimable functions. This method is based on the hierarchical Bayesian approach for estimating a vector of unknown parameters. Also, we verify that estimators obtained by our method are identical to least squares estimators of estimable functions obtained by using either generalized inverses or full rank reparametrization of the models. Some examples are given which illustrate our results.

• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.543-549
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• 2008

Inspired by using a robust loss function in the support vector machine regression to control training error and the idea of robust template matching with M-estimator, Chen (2004) applies M-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for the support vector machines. We are specially interested in the shape of the Huber's M-estimator in this context and propose a way to find the shape parameter of the Huber's M-estimating function. For simplicity, only the two-class classification problem is considered.

• 충청수학회지
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• 제24권2호
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• pp.319-335
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• 2011

We classify equivariant topoligical complex vector bundles over real projective plane under a compact Lie group (not necessarily effective) action. It is shown that nonequivariant Chern classes and isotropy representations at (at most) three points are sufficient to classify equivariant vector bundles over real projective plane except one case. To do it, we relate the problem to classification on two-sphere through the covering map because equivariant vector bundles over two-sphere have been already classified.

• Bulletin of the Korean Chemical Society
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• 제7권5호
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• pp.347-353
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• 1986

Fisher's discriminant method has been applied to the problem of the classification of Korean potsherds, using their elemental composition as analyzed by neutron activation analysis. A combination of analytical data by means of statistical linear discriminant analysis has resulted in removal of redundant variables, optimal linear combination of meaningful variables and formulation of classification rules.

• 대한지구과학교육학회지
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• 제5권3호
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• pp.256-266
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• 2012

The purpose of this study is to use DARTs (Directed Activities Related to text) to foster inquiry problems while actively engaging accelerated gifted elementary students in the field of earth sciences. This study is continually evolving in the classroom on the proposition that accelerate the scientific thought whether inquiry problems show any change according to the extent of prior background knowledge through DARTs. Researchers appointed the accelerated gifted elementary students with 14 investigation problems and it was their duty to not only classify the inquiry problems, but to analyze using interviewing methods according to type classification framework. Many scientific terms were used concretely in the inquiry problems that were propose after DART. The students gave a direct effect to the inquiry problem to be proposed according to the level of the content that it is presented in the DARTs worksheet. As a result, the NP-IP type and the EC-IP, NC-IP inquiry problem type proposed above much as a whole in DARTs former and prior. Particularly, the EMC-IP type and etc. was variously proposed after the DARTs. And the students proposing the inquiry problem of above average proposed the inquiry problem of the EP-IP type much unlike the general average student after the DARTs. The EC-IP, NC-IP and NF-IP type were changed much after DARTs used. Particularly, the EC-IP and NC-IP type were changed much.