• Journal of the Korean Geophysical Society
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• v.8 no.3
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• pp.153-157
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• 2005

A discussion of a method has been used with success in terrain modelling to estimate the height at any point on the land surface from irregularly distributed samples. The special requirements of terrain modelling are discussed as well as a detailed description of the algorithm and an example of its application.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.37-45
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• 1998

In this paper, we extracted heart region using dyamic contour model, increased the vertical resolution of heart region by proposed 2-dimensional interpolation method and visualized the 3-dimensional hearet volutme. the proposed new energy term of dynamic contour model considering the gray level and direction of controur vectors is effective to extract the closed heart boundary. And, we generatedvertical slice images from the extracted heart region images using the 2-dimensional linear interpolation by DT(distance transform). We showed that proposed algorithm is useful by 3-dimensional visualization of heart volume.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.145-153
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• 2015

This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.189-198
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• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.2
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• pp.17-22
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• 1990

The Digital Terrain Model(DTM) data in the Geographic Information System(GIS) needs to be interpolated for various purposes. Three interpolation methods-Bilinear, Bicubic Spline, and Gregory-Newton interpolation-were used, compared, and analyzed in terms of the visual comparison and numerical analysis in the hilly terrain and relatively flat terrain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2345-2354
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• 1998

There have been many researches to yield higher resolution image quality from the low resolution CCD device. The resolution of it is primary factor for the image quality of digital still camera and in manufacturing price. IN this paper, image enlargement algorithm, which reduces blocking effect of enlarged low resolution image and minimizes ringing and blur effect occurring around edge in linear interpolation, is proposed. This algorithm is composed of gaussian low pass filter which eliminates aliasing, least square spline interpolation and non-linear interpolation based on step edge model.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.872-878
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• 2018

Steam tables including superheated, saturated and compressed region were simultaneously modeled using the neural networks. Pressure and temperature were used as two inputs for superheated and compressed region. On the other hand Pressure and dryness fraction were two inputs for saturated region. The outputs were specific volume, specific enthalpy and specific entropy. The neural network model were compared with the linear interpolation model in terms of the percentage relative errors. The criterion of judgement was selected with the percentage relative error of 1%. In conclusion the neural networks showed better results than the interpolation method for all data of superheated and compressed region and specific volume of saturated region, but similar for specific enthalpy and entropy of saturated region.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.934-937
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• 2006

This investigation presents a topology formulation to design optimal poroelastic acoustic foams to maximize absorbing ability. For successful formulation, a single set of equations based on Biot's theory is adopted and an appropriate material interpolation strategy is newly developed. Because there was no earlier attempt to solve poroelastic acoustic foam design problems in topology optimization setting, many challenging issues including modeling and interpolation must be addressed. First, the simulation accuracy by a proposed unified model encompassing acoustic air and poroelastic material was checked against analytical and numerical results. Then a material interpolation scheme yielding a distinct acoustic air-poroelastic material distribution was developed. Using the proposed model and interpolation scheme, the topology optimization of a two-dimensional poroelastic acoustic foam for maximizing its absorption coefficient was carried out. Numerical results show that the absorption capacity of an optimized foam layout considerably increases in comparison with a nominal foam layout.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6C
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• pp.572-578
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• 2007

To establish eye contact in video teleconferencing, it is necessary to synthesize a front view image by viewpoint interpolation. We can find the viewing direction of a user, and interpolate an image seen from that viewpoint, which will result in a face image observed from the front. There are two categories of previous research: image based method and model based method. The former is simple to calculate, however, it shows limited performance for complex objects. And the latter is robust to noise while it is computationally expensive. We propose to approximate face images as ellipses and match them to build an ellipsoid and then synthesize a new image from a given virtual camera position. We show that it is simple and robust from various experiments.