• ETRI Journal
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• v.39 no.6
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3296-3314
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• 2012

We present a novel approach for the simulation of color pencil effects using line integral convolution (LIC) to produce pencil drawings from images. Our key idea is to use a bilateral convolution filter to simulate the various effects of pencil strokes. Our filter resolves the drawbacks of the existing convolution-based schemes, and presents an intuitive control to mimic the properties of pencil strokes. We also present a scheme that determines stroke directions from the shapes to be drawn. Smooth tangent flows are used for the pixels close to feature lines, and partially parallel flows inside regions. The background is rendered using a flow of fixed direction. Using different styles of stroke directions increases the realism of the resulting images. This approach produces convincing pencil drawing effects from photographs.

• The Journal of Korean Association of Computer Education
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• v.10 no.1
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• pp.97-105
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• 2007

In this paper, visualization of convolution operation is presented, which is implemented by scalable vector graphics (SVG). Convolution operation is one of the basic essential concepts in the area of signal and image processing. However, it is difficult for students to intuitively understand the operation of convolution since it is mainly based on mathematical representation. We present the visualization of convolution operation and its applications which are implemented by SVG. The effects of the proposed approach have been analyzed by interviews. It has been seen that the proposed visualization of convolution operation could be effectively applied to learn the convolution operation and its applications.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1037-1041
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• 2007

With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral psycho-acoustic filters considering masking effects are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for realtime implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.2
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• pp.231-237
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• 2008

With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral real-time masking blocks are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for real-time implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.1
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• pp.14-22
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• 1980

The Fourier convolution algorithm is used to reconstruct a 34 density function from projection data sets. The convolved data are then back-projected to obtain a density function. There are several choices of the weighting function for the design of the reconstruction(deblurring) filter. Present Paper reviews the published reconstruction liters theoretically and proposes a new reconstructirm filter design method, considering the problems such as the effects of sampling rate, aliasing, and noise. Several previous reconstructirn filters are compared with the proposed filter by computer simulations.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.155-157
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• 1979

The Fourier convolution algorithms are used to reconstruct a 3-D density function from the projection data sets. The convolved data are then back projected to obtain a density function. There are several choices of the weighting function for the design of the reconstruction(deblurring) filter. Present paper reviews the design of reconstruction filter considering the problems such as the effects of sampling rate, aliasing, and noise.

• Steel and Composite Structures
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• v.11 no.5
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• pp.403-421
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• 2011

In the present manuscript, geometrically nonlinear free vibration analysis of thin laminated plates resting on non-linear elastic foundations is investigated. Winkler-Pasternak type foundation model is used. Governing equations of motions are obtained using the von Karman type nonlinear theory. The method of discrete singular convolution is used to obtain the discretised equations of motion of plates. The effects of plate geometry, boundary conditions, material properties and foundation parameters on nonlinear vibration behavior of plates are presented.

• Smart Structures and Systems
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• v.30 no.1
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.621-634
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• 2009

A numerical method is developed to investigate the effects of some geometric parameters and density variation on frequency characteristics of the circular and annular membranes with varying density. The discrete singular convolution method based on regularized Shannon's delta kernel is applied to obtain the frequency parameter. The obtained results have been compared with the analytical and numerical results of other researchers, which showed well agreement.