• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.530-532
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• 2007

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed and discussed.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.831-834
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• 2008

The spectral element model is known to provide very accurate structural dynamic characteristics, while reducing the number of degree-of-freedom to resolve the computational and cost problems. Thus, the spectral element model with variational method for an axially moving Bernoulli-Euler beam subjected to axial tension is developed in the present paper. The high accuracy of the spectral element model is the verified by comparing its solutions with the conventional finite element solutions and exact analytical solutions. The effects of the moving speed and axial tension the vibration characteristics, wave characteristics, and the static and dynamic stabilities of a moving beam are investigated.

• 한국인쇄학회:학술대회논문집
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• 한국인쇄학회 1998년도 추계 논문 발표회 논문집
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• pp.16-21
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• 1998

Spectral reflrectance of the object should be mesured to predict the color of object under various illuminants. The spectral reflectance can be represented in a multidemensional space; Generally we can obtain only three-channel data from input device such as CCD camera, color scanner etc. The estimation from three dimernsional to multidimension can be achieved using principal components of spectral reflectance. In this paper, A method to predict the spectral reflectance of skin color taken by 3-channel input device is discribed. To confirm this method, we simulate color represent under various illuminants about yellow, white and colored women face.

• ETRI Journal
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• 제39권6호
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• pp.832-840
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• 2017

Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception-based spatial and spectral-domain noise-reduced harmonic features are extracted from multichannel audio and used as high-resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short-term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

• 항공우주기술
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• 제12권1호
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• pp.152-162
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• 2013

달의 방사조도는 위성 가시채널 검출기의 성능을 감시하기 위해서 사용된다. 본 논문에서는 천리안위성 FDS (Flight Dynamics Subsystem)에서 생성한 태양, 달, 위성의 위치 정보를 이용하여 달의 방사조도를 계산하는 방법 및 결과를 설명한다. 계산 결과는 천리안위성 기상탑재체 가시채널 검출기의 성능저하를 검출하고 보상하기 위한 알고리즘에 적용되었다.

• 대한전기학회논문지
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• 제44권6호
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• pp.799-805
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• 1995

An infrared radiator of cordierite system were manufactured byslurry casting anddry pressing method. The characteristics of cordierite (2MgO.2Al$_{2}$O$_{3}$.5SiO$_{2}$)+30wt% clay+Xwt% MnO$_{2}$ of infrared radiator have been investigated as a function of MnO$_{2}$ additives (X=0, 0.1, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5). The thermal expansioncoefficient was decreased with increasing amounts of MnO$_{2}$ additives. Otherwise, the spectral emissivity was increased in the below 4.5.mu.m wavelength. Also, the infrared radiator of cordierite system which spectral emissivity was approximately 1.0 can be attainable at from 4.5.mu.m to 8.mu.m wavelength. The spectral emissivity was decreased from 8.mu.m to 14.mu.m above X=2.5.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (1)
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• pp.697-699
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• 2004

Despite many successful spectral clustering algorithm (based on the spectral decomposition of Laplacian(1) or stochastic matrix(2) ) there are several unsolved problems. Most spectral clustering Problems are based on the normalized of algorithm(3) . are close to the classical graph paritioning problem which is NP-hard problem. To get good solution in polynomial time. it needs to establish its convex form by using relaxation. In this paper, we apply a novel optimization technique. semidefinite programming(SDP). to the unsupervised clustering Problem. and present a new multiple Partitioning method. Experimental results confirm that the Proposed method improves the clustering performance. especially in the Problem of being mixed with non-compact clusters compared to the previous multiple spectral clustering methods.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.218-227
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• 2018

Vocal effort detection is important for both robust speech recognition and speaker recognition. In this paper, the spectral information entropy feature which contains more salient information regarding the vocal effort level is firstly proposed. Then, the model fusion method based on complementary model is presented to recognize vocal effort level. Experiments are conducted on isolated words test set, and the results show the spectral information entropy has the best performance among the three kinds of features. Meanwhile, the recognition accuracy of all vocal effort levels reaches 81.6%. Thus, potential of the proposed method is demonstrated.

• 대한기계학회논문집
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• 제18권1호
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• pp.166-174
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• 1994

A critical evaluation is made of the spectral bias which occurs in the use of a laser doppler velocimeter(LDV). Two processing algorithms are considered for spectral estimates: the sample and hold interpolation method(SH) and the nonuniform Shannon reconstruction technique(SR). Assessment is made of these for varying data densities $(0.05{\le}d.d.{\le}5)$ and turbulence levels(t.i.=30%, 100%). As an improved version of the spectral estimator, the utility of POCS (the projection onto convex sets) has been tested in the present study. This algorithm is found useful to be in the region when $d.d.{\gep}3.$