• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.71-76
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• 2022

The article aims to consider the role of computer technologies in contemporary jewelry art. The importance of computer programming, 3D-modeling and 3D-printing for the process of jewelry creating, its advertising and sales is emphasized. Both the positive features of the possibility of using computer technologies in jewelry and their shortcomings are considered. The process of changing the nature of jewelry design after the start of the use of digital technologies is highlighted. The issue of changing the perception and evaluation of a work of jewelry art, the creation of which uses mechanization, has been updated.

• The Korean Journal of Zoology
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• v.39 no.1
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• pp.26-35
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• 1996

The projection from the lateral reticular nucleus (LRN) to three subdivisions of the cerebellar vermal lobule VI was studied in the rat by utilizing the retrograde transport of wheatgerm agglutinin-conjugated horseradish peroxidase. Labelled neurons were located bilaterally throughout the LRN, but with ipsilateral predominance. There seemed to be a dorsal4o-ventral transition in the ipsilateral magnocellular neurons projecting to the cerebellar vermal lobules VIa-to-Vic. In the contralateral side, cells projecting to vermal lobule Via were observed at more rostral sections, whereas those projecting to lobule Vic were located at caudal sections. There were relatively few labelled neurons in parvocellular or subtrigeminal divisions at either side. Computer-aided three dimensional reconstruction of LRN projections to lobules Via/Vib or lobules Vib/Vic exhibited extensive oberlap within each combination of injection cases.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.786-790
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• 2007

Up to now, surgeons have operated while peering at images which visualize the medical state of the patient such as MRI or CT images. On the other hand, direct-projected augmented reality technology liberates surgeons from the inconvenience by directly projecting medical information onto the patient's body. However surgeons still feel inconvenient when they mark surgical targets for planning an operation because they use an ink pen which is difficult to modify or delete and is also likely to be unsanitary. In this paper, we resolve these problems by proposing an interactive user interface based on direct-projected augmented reality technology and its validity is shown in experimental results.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.25-32
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• 2021

Direct Volume Rendering(DVR) renders by projecting data into a two-dimensional space without calculating the volume surfaces. In DVR, the transfer function(TF) assigns light properties such as color and transparency to the volume. However, it takes a long time for beginners to manipulate TF to understand volume data and assign colors. This paper proposes an approach to colorize the volume using sample images for intuitive volume rendering. We also discuss color extraction methods using K-means clustering.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.289-294
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• 2017

In this paper, we implement to make the character content with the floating hologram. The floating hologram is the one of hologram techniques for projecting the 2D image to represent the 3D image in the air using the glass panel. The floating hologram technique is easy to apply and is used in exhibitions, corporate events, and advertising events. This paper uses both the depth information and the unreal engine for the floating hologram. Simulation results show that this method can make the character content to follow the movement of the user in the real time by capturing the depth video.

• International Journal of Contents
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• v.14 no.4
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• pp.24-29
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• 2018

EEG-based brain-computer interfaces has focused on explicitly expressed intentions to assist physically impaired patients. For EEG-based-computer interfaces to function effectively, it should be able to understand users' implicit information. Since it is hard to gather EEG signals of human brains, we do not have enough training data which are essential for proper classification performance of implicit intention. In this paper, we improve the subject independent classification of implicit intention through the generation of additional training data. In the first stage, we perform the PCA (principal component analysis) of training data in a bid to remove redundant components in the components within the input data. After the dimension reduction by PCA, we train ICA (independent component analysis) network whose outputs are statistically independent. We can get additional training data by adding Gaussian noises to ICA outputs and projecting them to input data domain. Through simulations with EEG data provided by CNSL, KAIST, we improve the classification performance from 65.05% to 66.69% with Gamma components. The proposed sample generation method can be applied to any machine learning problem with fewer samples.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.626-637
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• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.123-127
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• 2004

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1107-1115
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• 1997

In this paper, we propose an error concealment method to recovre damaged block-based image coding schemes. Channel errors during transmission of image data such as bit errors or cell loss result in damaged image blocks in the reconstructed images. To recover damaged blocks is to estimate them using the correctly received or undamaged neighborhood information. In the proposed method, an overcomplete basis for a large block containing a damaged block at its center is introduced and damaged blocks are recovered by sequentially projecting the known neighborhood information onto the overcomplete basis function. Computer simulations show that the proposed algorithm outperforms the conventional method in subjectie recovery qualities as well as objective ones.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.51-56
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• 2016

In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.