• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.980-993
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• 2020

Deep-learning based style transfer has recently attracted great attention, because it provides high quality transfer results by appropriately reflecting the high level structural characteristics of images. This paper deals with the problem of providing more stable and more diverse style transfer results of such deep-learning based style transfer method. Based on the investigation of the experimental results from the wide range of hyper-parameter settings, this paper defines the problem of the stability and the diversity of the style transfer, and proposes a partial loss normalization method to solve the problem. The style transfer using the proposed normalization method not only gives the stability on the control of the degree of style reflection, regardless of the input image characteristics, but also presents the diversity of style transfer results, unlike the existing method, at controlling the weight of the partial style loss, and provides the stability on the difference in resolution of the input image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.11
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• pp.870-878
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• 2013

The objective of this paper is to develop mobile-based PACS(Picture Archiving Communication System: mPACS) for diagnostic medical image service available via Android-based mobile smartphone. The proposed mPACS provides an integrated platform for mobile application of diagnostic medical images stored in hospital PACS, and allows the smartphone to store, retrieve, manipulate and transfer the diagnostic medical images. Then, the mPACS platform includes the following features for use in the Android framework (i. e., diagnostic medical image processing) : transfer protocols between PACS, mPACS and smartphone, image format converter, JPEG and JPEG2000 coders, text and avatar search, and etc. This mPACS is shown to be useful and effective in providing a solution for mobile-based diagnostic medical image service.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.2
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• pp.212-218
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• 2013

A transfer method of neutron radiography was developed to measure the size of the end plug and a gap of an intact K102L-2, the irradiated fuel of a ballooned K174L-3, a ballooned and ruptured K98L-3. A typical irradiation time of 25 min. was determined to obtain a film density of between 2 and 3 of SR X-ray film with neutrons of $1.5{\times}10^{11}n{\cdot}cm^{-2}$. To validate and calibrate the results, a RISO fuel standard sample, Cd plate and ASTM-BPI/SI were used. An activated latent image formed in the $100{\mu}m$ Dy foil was subsequently transferred in a dark room for more than 8 hours to the SR film which is a maximum of three half-lives. Due to the L/D ratio an unsharpness of $9.82-14{\mu}m$ and a magnification of 1.0003 were given. After digitizing an image of SR film, the ballooning gap of the plug was discernible by an H/V filter of image processing. The gap size of the ballooned element, K174L-3, is equal to or greater than 1.2 mm. The development of a transfer method played a pivotal role in developing high burn-up of Wolsung and PWR nuclear fuel type.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.399-407
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• 2019

In Korea, the construction industry has been known to have the highest risk of safety accidents compared to other industries. Therefore, in order to improve safety in the construction industry, several researches have been carried out from the past. This study aims at improving safety of labors in construction site by constructing an effective automatic safety helmet detection system using object detection algorithm based on image data of construction field. Deep learning was conducted using Region-based Fully Convolutional Network (R-FCN) which is one of the object detection algorithms based on Convolutional Neural Network (CNN) with Transfer Learning technique. Learning was conducted with 1089 images including human and safety helmet collected from ImageNet and the mean Average Precision (mAP) of the human and the safety helmet was measured as 0.86 and 0.83, respectively.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.623-632
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• 2008

In this paper, we used the color transfer function and the opacity transfer function for the internal 3D object visualization of an image volume data. In transfer function, creating values of between boundaries generally is ambiguous. We concentrated to extract boundary features for segmenting the visual volume rendering objects. Consequently we extracted an image gradient feature in spatial domain and created a multi-dimensional transfer function according to the GPU efficient improvement. Finally using these functions we obtained a good research result as an implementing object boundary visualization of the graphic hardware based 3D texture mapping.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.8
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• pp.1566-1574
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• 1992

Local heat transfer characteristics for a round air jet impinging normally on a heated flat plate were experimentally investigated. The problem parameters investigated were jet Reynolds number, Re=4000,10000, and 20000, and nozzle-to-plate spacing(L/D) of 2,6, and 10. The temperature variations on the flat uniform heat flux surface were mapped using a thermo-sensitive liquid crytal sheet. The isochromatic images corresponding to the characteristic temperature of liquid crystal were analyzed with the help of a digital image processing system. The local Nusselt number, Nu decreased rapidly in the impingement region and exhibited a similar profiles in the wall jet region independent of the nozzle-to-plate spacing L/D. In the case of large Reynolds number, heat transfer rate (Nu) was proportional to 0.5 power of the Reynolds number. For L/D=2, a secondary peak in the heat transfer rate was seen in the region of X/D=1.5~3 due to the transition from laminar to turbulent boundary layer.

• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.513-517
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• 2013

Recently, maskless lithography (ML) systems have become popular in digital manufacturing technologies. To achieve high-throughput manufacturing processes, digital micromirror devices (DMD) in ML systems must be driven to their operational limits, often in harsh conditions. We propose an instrument and algorithm to detect DMD malfunctions to ensure perfect mask image transfer to the photoresist in ML systems. DMD malfunctions are caused by either bad DMD pixels or data transfer errors. We detect bad DMD pixels with $20{\times}20$ pixel by white and black image tests. To analyze data transfer errors at high frame rates, we monitor changes in the frame rate of a target DMD pixel driven by the input data with a set frame rate of up to 28000 frames per second (fps). For our data transfer error detection method, we verified that there are no data transfer errors in the test by confirming the agreement between the input frame rate and the output frame rate within the measurement accuracy of 1 fps.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.149-158
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• 2024

Traditional manual identification of crop leaf diseases is challenging. Owing to the limitations in manpower and resources, it is challenging to explore crop diseases on a large scale. The emergence of artificial intelligence technologies, particularly the extensive application of deep learning technologies, is expected to overcome these challenges and greatly improve the accuracy and efficiency of crop disease identification. Crop leaf disease identification models have been designed and trained using large-scale training data, enabling them to predict different categories of diseases from unlabeled crop leaves. However, these models, which possess strong feature representation capabilities, require substantial training data, and there is often a shortage of such datasets in practical farming scenarios. To address this issue and improve the feature learning abilities of models, this study proposes a deep transfer learning adaptation strategy. The novel proposed method aims to transfer the weights and parameters from pre-trained models in similar large-scale training datasets, such as ImageNet. ImageNet pre-trained weights are adopted and fine-tuned with the features of crop leaf diseases to improve prediction ability. In this study, we collected 16,060 crop leaf disease images, spanning 12 categories, for training. The experimental results demonstrate that an impressive accuracy of 98% is achieved using the proposed method on the transferred ResNet-50 model, thereby confirming the effectiveness of our transfer learning approach.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.591-603
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• 2008

Satellite performance can be evaluated by image quality. MTF(Modulation Transfer Fuction), SNR(Signal To Noise Ratio), GSD(Ground Sample Distance) etc. are important bias parameters to analyze image quality. It is necessary to estimate quality of satellite image in design stage. In this paper, the simulating method of satellite image quality, considering design, manufacturing, and operation, is proposed. The proposed method shall be used to estimate and restore quality of satellite image.

• Conservation Science in Museum
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• v.31
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• pp.55-70
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• 2024

Style transfer algorithms are currently undergoing active research and are used, for example, to convert ordinary images into classical painting styles. However, such algorithms have yet to produce appropriate results when applied to Korean cultural heritage images, while the number of cases for such applications also remains insufficient. Accordingly, this study attempts to develop a style transfer algorithm that can be applied to styles found among Korean cultural heritage. The algorithm was produced by improving data comprehension by enabling it to learn meaningful characteristics of the styles through representation learning and to separate the cultural heritage from the background in the target images, allowing it to extract the style-relevant areas with the desired color and texture from the style images. This study confirmed that, by doing so, a new image can be created by effectively transferring the characteristics of the style image while maintaining the form of the target image, which thereby enables the transfer of a variety of cultural heritage styles.