• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.9-17
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• 2021

With the advancement of big data analysis, artificial intelligence, machine learning, etc., data analytics technology has developed to help with optimal decision-making. However, in certain areas, the lack of data restricts the use of these techniques. For example, real estate related data often have a long release cycle because of its recent release or being a non-liquid asset. In order to overcome these limitations, we studied the scalability of the existing time series through the TimeGAN model. A total of 45 time series related to weekly real estate data were collected within the period of 2012 to 2021, and a total of 15 final time series were selected by considering the correlation between the time series. As a result of data expansion through the TimeGAN model for the 15 time series, it was found that the statistical distribution between the real data and the extended data was similar through the PCA and t-SNE visualization algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.740-753
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• 2023

Text recognition in natural scene images is a challenging problem in computer vision. The accurate identification of ship number characters can effectively improve the level of ship traffic management. However, due to the blurring caused by motion and text occlusion, the accuracy of ship number recognition is difficult to meet the actual requirements. To solve these problems, this paper proposes a dual-branch network based on the CRNN identification network. The network couples image restoration and character recognition. The CycleGAN module is used for blur restoration branch, and the Pix2pix module is used for character occlusion branch. The two are coupled to reduce the impact of image blur and occlusion. Input the recovered image into the text recognition branch to improve the recognition accuracy. After a lot of experiments, the model is robust and easy to train. Experiments on CTW datasets and real ship maps illustrate that our method can get more accurate results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1305-1311
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• 2022

With the recent rapid development of mobile terminals and personal computers and the advent of neural network technology, real-time face swapping using images has become possible. In particular, the cycle generative adversarial network made it possible to replace faces using uncorrelated image data. In this paper, we propose an input data processing scheme that can improve the quality of face swapping with less training data and time. The proposed scheme can improve the image quality while preserving facial structure and expression information by combining facial landmarks extracted through a pre-trained neural network with major information that affects the structure and expression of the face. Using the blind/referenceless image spatial quality evaluator (BRISQUE) score, which is one of the AI-based non-reference quality metrics, we quantitatively analyze the performance of the proposed scheme and compare it to the conventional schemes. According to the numerical results, the proposed scheme obtained BRISQUE scores improved by about 4.6% to 14.6%, compared to the conventional schemes.

• The Journal of Korean Obstetrics and Gynecology
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• v.33 no.3
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• pp.175-186
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• 2020

Objectives: The purpose of this study is to report the effect of Jokyeongjongok-tang-gami in case of oligomenorrhea patients classified with gan-ulgiche and eumheo due to polycystic ovary syndrome. Methods: Three patients suffering from oligomenorrhea due to polycystic ovary syndrome were treated with korean medical treatment (herbal medicine, moxibustion, acupuncture) more than 3 months. The patients classified with gan-ulgiche and eumheo were treated with Jokyeongjongok-tang-gami. Results: Three oligomenorrhea patients recovered normal menstrual cycle more than 3 times after taking Korean medical treatment for 3~6 months. Conclusions: This 3 cases classified with gan-ulgiche and eumheo show Jokyeongjongok-tang-gami is effective on patients with rare menstruation due to polycystic ovary syndrome.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.663-672
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• 2023

Most vehicle detection methods have poor vehicle feature extraction performance at night, and their robustness is reduced; hence, this study proposes a night vehicle detection method based on style transfer image enhancement. First, a style transfer model is constructed using cycle generative adversarial networks (cycleGANs). The daytime data in the BDD100K dataset were converted into nighttime data to form a style dataset. The dataset was then divided using its labels. Finally, based on a YOLOv5s network, a nighttime vehicle image is detected for the reliable recognition of vehicle information in a complex environment. The experimental results of the proposed method based on the BDD100K dataset show that the transferred night vehicle images are clear and meet the requirements. The precision, recall, mAP@.5, and mAP@.5:.95 reached 0.696, 0.292, 0.761, and 0.454, respectively.

• East Asian Economic Review
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• v.23 no.2
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• pp.203-223
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• 2019

This paper examines the interactions between financial conditions and business cycles in Mongolia, a small open economy, heavily depending on commodity exports. We construct two financial conditions indexes based on the reduced form IS model and the vector autoregression (VAR) model as surveillance tools to quantify the degree of the financial conditions. We find that real short-term interest rate and real effective exchange rate gap get a higher weight in the FCIs. Both business and financial cycles are often more pronounced in Mongolia, and financial condition is dependent of the financial and monetary policies in place. The analysis of the predictive power of the FCIs for business cycles shows that they have predictive information for the near-term economic activities. FCIs are also helpful in signaling inflation turning points.

• Journal of Korea Multimedia Society
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• v.23 no.7
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• pp.850-861
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• 2020

Hangul is a language that is composed of initial, medial, and final syllables. It has 11,172 characters. For this reason, the current method of designing all the characters by hand is very expensive and time-consuming. In order to solve the problem, this paper proposes an automatic Hangul font generation system and evaluates the standards for mapping Hangul characters to produce an effective automated Hangul font generation system. The system was implemented using character generation engine based on deep learning CycleGAN. In order to evaluate the criteria when mapping characters in pairs, each criterion was designed based on Hangul structure and character shape, and the quality of the generated characters was evaluated. As a result of the evaluation, the standards designed based on the Hangul structure did not affect the quality of the automated Hangul font generation system. On the other hand, when tried with similar characters, the standards made based on the shape of Hangul characters produced better quality characters than when tried with less similar characters. As a result, it is better to generate automated Hangul font by designing a learning method based on mapping characters in pairs that have similar character shapes.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.535-546
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• 2019

Recently, there have been a lot of researches on the whole face replacement system, but it is not easy to obtain stable results due to various attitudes, angles and facial diversity. To produce a natural synthesis result when replacing the face shown in the video image, technologies such as face area detection, feature extraction, face alignment, face area segmentation, 3D attitude adjustment and facial transposition should all operate at a precise level. And each technology must be able to be interdependently combined. The results of our analysis show that the difficulty of implementing the technology and contribution to the system in facial replacement technology has increased in facial feature point extraction and facial alignment technology. On the other hand, the difficulty of the facial transposition technique and the three-dimensional posture adjustment technique were low, but showed the need for development. In this paper, we propose four facial replacement models such as 2-D Faceswap, OpenPose, Deekfake, and Cycle GAN, which are suitable for the Cox platform. These models have the following features; i.e. these models include a suitable model for front face pose image conversion, face pose image with active body movement, and face movement with right and left side by 15 degrees, Generative Adversarial Network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• Economic and Environmental Geology
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• v.4 no.2
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• pp.77-90
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• 1971

About four hundred deposits of iron, talc, fluorite, tungsten, molybdenum, lead, zinc and other polymetallic mineral deposits were plotted on the Ore Distribution Map of the Ockcheon Geosynclinal Area. These mineral deposits plotted on the map can be divided into the several metallogenic zones by the consideration of their geologic background including the sedimentary and tectonic cycles and the igneous activities in the geosynclinal evolution, as follows: a. Chungju iron and talc zones. b. Cheong-san copper bearing iron sulphide zone c. Kumsan-Muju fluorite-polymetallic zones. d. Cheong-an Puyong and Ein Suckseong gold zone e. Hwang-gan Seolcheon and Sangju gold zones. Chungju iron zone originated in the iron bed in the Kemyongsan Series corresponding to the Pre-Ockcheon Cycle of evolution history. In early period of the Ockcheon Cycle, Hyangsanri quartzite and Munjuri phyllitic formation corresponding to the lower terrigenous sequence were not mineralized while the next sequence of the Samsungsan basic igneous-metamorphic formation and the Changri limestone formation were mineralized by the copper bearing iron sulphide and the fluorite-polymetallic deposits respectively. Two generations of the gold zones are recognized. The earlier generation distributes directionaly in the outside of the Ockcheon sedimentary belt was followed by the earlier grantitic invasion of Jurasic in age, while the later generation scatters at random which was related to the nondirectional Cretaceous granitic intrusion of the Post-Ockcheon Cycle. Conclusively speaking, it was disclosed that the endogenic mineralization in the Ockcheon geosyn clinal zone was not conspicuous in its inner sedimentary belt except its limestone area but in its outer peripheral granitic or gneissic zones, and the related igneous activities occured in the Post-Ockcheon Cycle of evolution history.