• 조형예술학연구
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• 제4권
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• pp.123-146
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• 2002

[ $\lceil$ ]The Life of Pigeons$\rfloor$ consists of seven different canvases without a leading image It contains fragments of disassociated ordinary subjects from a capitalistic and consuming society. In this respect, the text itself attains multiple meanings throughout with inner disharmony, disassociation and relationships of differences. The divided seven images look as if they are connected as one and are connected events that are happening at the same time and in similar places. A liberal interpretation of this work is given to viewers when the seven canvases have both relations and gaps at the same time. $\lceil$The Life of Pigeons$\rfloor$ attempts the viewer's disruption through its middle stratum of meaning structure, which is a device for viewers to rearrange and deeply analyze the seven images. As a result, the artist allows the viewers to get lost in self-contradiction. A fundamental formal structure adopting post-modernism and abandoning modernism is what we can detect with detailed analysis of the work. For instance, changing surface style appears by dividing or putting images in obliquely, furthermore it clearly shows that the main subject is divided in form such as the subject's division into seven spaces. There are three major characteristics. First, the form of the images is divided and composed through oblique and overlapped images. Second, the main content of the subject tends to be scattered. Third, the subjects are interpreted in multiple meanings due to their allegory and symbolism. The inquiry of $\lceil$The Life of Pigeons$\rfloor$ proves that it takes a post artistic spirituality as its basis and its subjects are divided by the differences and surrounding relationships.

• Korean Journal of Radiology
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• 제20권6호
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• pp.976-984
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• 2019

Objective: To establish diagnostic criteria for pulmonary arterial hypertension (PAH) in children by using parameters obtained through noninvasive cardiac computed tomography (CCT). Materials and Methods: We retrospectively measured parameters from CCT images of children from a single institution in a multiple stepwise process. A total of 208 children with mean age of 10.5 years (range: 4 days-18.9 years) were assessed. The variables were classified into three groups: the great arteries; the ventricular walls; and the bilateral ventricular cavities. The relationship between the parameters obtained from the CCT images and mean pulmonary arterial pressure (mPAP) was tested and adjusted by the children's body size. Reference curves for the pulmonary trunk diameter (PTD) and ratio of diameter of pulmonary trunk to ascending aorta (rPTAo) of children with CCT images of normal hearts, adjusted for height, were plotted. Threshold lines were established on the reference curves. Results: PTD and rPTAo on the CCT images were significantly positively correlated with mPAP (r > 0.85, p < 0.01). Height was the body size parameter most correlated with PTD (r = 0.91, p < 0.01) and rPTAo (r = -0.69, p < 0.01). On the basis of the threshold lines on the reference curves, PTD and rPTAo both showed 88.9% sensitivity for PAH diagnosis, with negative predictive values of 93.3% and 92.9%, respectively. Conclusion: PTD and rPTAo measured from CCT images were significantly correlated with mPAP in children. Reference curves and the formula of PTD and rPTAo adjusted for height could be practical for diagnosing PAH in children.

• Journal of Computing Science and Engineering
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• 제2권1호
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• pp.98-108
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• 2008

Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (REFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.

• 대한수학회지
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• 제47권3호
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• pp.445-454
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• 2010

The braid group $B_n$ maps homomorphically into the Temperley-Lieb algebra $TL_n$. It was shown by Zinno that the homomorphic images of simple elements arising from the dual presentation of the braid group $B_n$ form a basis for the vector space underlying the Temperley-Lieb algebra $TL_n$. In this paper, we establish that there is a dual presentation of Temperley-Lieb algebras that corresponds to the dual presentation of braid groups, and then give a simple geometric proof for Zinno's theorem, using the interpretation of simple elements as non-crossing partitions.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.34-37
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• 2005

An efficient and robust neural network-based scheme is introduced in this paper to perform automatic cloud detection. Unlike many existing cloud detection schemes which use thresholding and statistical methods, we used the artificial neural network methods, the multi-layer perceptrons (MLP) with back-propagation algorithm and radial basis function (RBF) networks for cloud detection from Geostationary satellite images. We have used a simple scene (a mixed scene containing only cloud and clear sky). The main results show that the neural networks are able to handle complex atmospheric and meteorological phenomena. The experimental results show that two methods performed well, obtaining a classification accuracy reaching over 90 percent. Moreover, the RBF model is the most effective method for the cloud classification.

• 한국정보전자통신기술학회논문지
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• 제9권6호
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• pp.519-525
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• 2016

This paper addresses the framework of object-oriented image coding, describing a new algorithm, based on monodimensional Legendre polynomials, for texture approximation. Through the use of 1D orthogonal basis functions, the computational complexity which usually makes prohibitive most of 2D region-oriented approaches is significantly reduced, while only a slight increment of distortion is introduced. In the aim of preserving the bidimensional intersample correlation of the texture information as much as possible, suitable pseudo-bidimensional basis functions have been used, yielding significant improvements with respect to the straightforward 1D approach. The algorithm has been experimented for coding still images as well as motion compensated sequences, showing interesting possibilities of application for very low bitrate video coding.

• Journal of information and communication convergence engineering
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• 제2권4호
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• pp.251-255
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• 2004

In this paper, we present a watermarking scheme based on the DWT (Discrete Wavelet Transform) and the ANN (Artificial Neural Network) to ensure the copyright protection of the digital images. The problem to embed watermark is not clear to select important coefficient in the watermarking. We used the RBF (Radial-Basis Function) to solve the problem. We didn't apply the whole wavelet coefficients, but applied to only the wavelet coefficients in the selected node. Using the ANN, although even the watermark casting process and watermark verification process are in public, nobody knows the location of embedding watermark except of authorized user. As the result, the watermark is good at the strength test-filtering, geometric transform and etc.

• 한국정보통신학회논문지
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• 제6권6호
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• pp.986-991
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• 2002

본 논문에서는 고유벡터를 이용한 오프라인 필기체 숫자인식 기법을 제시한다. 본 기법에서는 KL 변환에 의한 고유벡터를 이용하여 통계적으로 숫자의 특징을 추출하며, 특징공간상에서 최소거리기법으로 숫자를 인식한다. 본 기법에서 제안된 특징추출 방법에서는 많은 표본 숫자영상에서 각 숫자들의 특징을 가장 잘 표현하는 기저벡터를 찾아내고 이로부터 숫자의 특징을 구한다. 제시된 기법의 성능 평가를 위해 Concordia대학의 무제약 필기체 숫자 데이터베이스를 사용하여 실험한 결과 96.2%의 인식률을 얻을 수 있었다.

• ETRI Journal
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• 제39권6호
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• pp.841-850
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• 2017

We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.

• 한국컴퓨터그래픽스학회논문지
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• 제9권3호
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• pp.15-21
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• 2003

An algorithm is developed for augmenting a real video with virtual graphics objects without computing Euclidean information. Real motion of the camera is obtained in affine space by a direct linear method using image matches. Then, virtual camera is provided by determining the locations of four basis points in two input images as initialization process. The four pairs of 2D location and its 3D affine coordinates provide Euclidean orthographic projection camera through the whole video sequence. Our method has the capability of generating views of objects shaded by virtual light sources, because we can make use of all the functions of the graphics library written on the basis of Euclidean geometry. Our novel formulation and experimental results with real video sequences are presented.