• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.53.3-53.3
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• 2019

Recent work by Ravanbakhsh et al. (2017), Mathuriya et al. (2018) showed that convolutional neural networks (CNN) can be trained to predict cosmological parameters from the visual shape of the large scale structure, i.e. the filaments, clusters and voids of the cosmic density field. These preliminary works used the dark matter density field at redshift zero. We build upon these works by considering realistic mock galaxy catalogues that mimic true observations. We construct light-cones that span the redshift range appropriate for current and near future cosmological surveys such as LSST, EUCLID, WFIRST etc. In summary, we propose a novel multi-image input CNN to track the evolution in the morphology of large scale structures over cosmic time to constrain cosmology and the expansion history of the Universe.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.28-31
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• 2002

Filmless full-PACS in korea has rapidly been growing, since government had supported collaborative PACS project between industry and university hospital in late of 1995. At the same time, a small company had started PACS business, while the Korea PACS society was being formed. In the beginning, PACS societies had focused on developing peripheral solutions such as DICOM gateway for image acquisition, x-ray film digitizer, and viewing software for research or management of personal image data, while Samsung Medical Center had started installing an imported partial PACS system which had recently upgraded with a new system. In similar time frame, a few hospitals had started developing and installing domestic large scale full-PACS system. Several years later, many hospitals have installed full-PACS system with national policy of reimbursement for PACS exams in November 1999. It is believed that Korea is the first country that adopted PACS reimbursement for filmless full-PACS as a national policy. Both experiences of full-PACS installation and national policy generated tremendous intellectual and technological expertise about PACS at all levels, clinical, hospital management, education, and industrial sectors. There are currently three types of PACS system which includes domestic, imported, and hybrid PACS system with imported solution for core system and domestic solution for peripheral system. There are more than 20 domestic PACS companies and they have now enough experiences so that they are capable of installing a truly full-PACS system for large-scale teaching hospitals. PACS societies in Korea understand how to design, implement, install, manage, sustain, and provide good services for large-scale full-PACS. PACS society has also strength for the highest integration technology of the Hospital Information. However, further understanding and timely implementation of continuously evolving international standard and integrated healthcare enterprise concepts may be necessary for international leading of PACS technologies for the future.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.17 no.3
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• pp.233-240
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• 2013

Objectives The objective and universal grading system for the facial nerve palsy is needed to the objectification of treatment in Oriental medicine. In this study, the facial nerve palsy grading was developed with combination of image processing technique and Nottingham scale. Methods The developed system is composed of measurement part, image processing part, facial nerve palsy evaluation part, and display part. With the video data recorded by webcam at measurement part, the positions of marker were measured at image processing part. In evaluation part, Nottingham scales were calculated in four different facial expressions with measured marker position. The video of facial movement, time history of marker position, and Nottingham scale were displayed in display part. Results & Conclusion The developed system was applied to a normal subject and a abnormal subject with facial nerve palsy. The left-right difference of Nottingham scores was large in the abnormal compared with the normal. In normal case, the change of the length between supraorbital point and infraorbital point was larger than that of the length between lateral canthus and angle of mouth. The abnormal case showed an opposite result. The developed system showed the possibilities of the objective and universal grading system for the facial nerve palsy.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.101-102
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• 2005

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.48-58
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• 2022

Blind restoration for motion-blurred images is always the research hotspot, and the key for the blind restoration is the accurate blur kernel (BK) estimation. Therefore, to achieve high-quality blind image restoration, this thesis presents a novel windowed-total-variation method. The proposed method is based on the spatial scale of edges but not amplitude, and the proposed method thus can extract useful image edges for accurate BK estimation, and then recover high-quality clear images. A large number of experiments prove the superiority.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.313-321
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• 2002

Supplying high-resolution satellite image, we take much interest in the update and the revision of digital map and thematic map based on the satellite image. This study presented the possibility of the update and the revision to the existing digital map on a scale of l/5,000 and 1/25,000 to take advantage of the IKONOS satellite image. We performed geometric correction to make use of the ground control points of the existing digital map in IKONOS mono-image and created ortho-image by extracting digital elevation model from three dimensional contour data and altitude on the existing digital map. We revised changed features in the method of screen digitizing by overlapping orthorectified satellite image and existing digital map and flawed features of the unchanged area on the satellite images for positional accuracy analysis. As a result, rectification error is calculated at $\pm$3.35m by RMSE. There is a good possibility of update of digital map under the scale of 1/10,000. It is possible to the update of the large scale digital map over the scale of l/5,000, as if we used the method of stereo image and ground control point surveying.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.321-326
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• 2003

The subjects of this study are to examine and to apply the methods of making 1:5,000 scale maps using 1m resolution stereo images of IKONOS for the Munsan area of Paju-city where aerial photo surveying cannot possible because of security conditions. GCP(Ground Control Point) were acquired from GPS surveying and were to perform geometric corrections on images. Digital Map used IKONOS stereo images and it worked from the digital analytical stereoplotter. From field investigation, RMSE errors of the plane and vertical positions are estimated to 1.706m and 1.231m, respectively. The plane accuracy is better than an accuracy required by NGIS (national GIS) programs. Local information from field investigation was added and the resulting maps should be good as digital map under the scale of 1/5,000.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2359-2376
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• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.

• Annual Conference of KIPS
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• 2010.04a
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• pp.405-408
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• 2010

This paper presents a new feature extraction technique, correlation coefficient and Manhattan distance (MD) based method for recognition of rotated object in an image. This paper also represented a new concept of intensity invariant. We extracted global features of an image and converts a large size image into a one-dimensional vector called circular feature vector's (CFVs). An especial advantage of the proposed technique is that the extracted features are same even if original image is rotated with rotation angles 1 to 360 or rotated. The proposed technique is based on fuzzy sets and finally we have recognized the object by using histogram matching, correlation coefficient and manhattan distance of the objects. The proposed approach is very easy in implementation and it has implemented in Matlab7 on Windows XP. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated images.

• Journal of Distribution Science
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• v.10 no.6
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• pp.17-26
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• 2012

Suncheon is a city comprising a rural and urban area, where there are four types of large stores. Studies have shown that there are too many large stores serving the local population of just 300,000. However, geographically, Suncheon is located at a transportation hub that borders the cities of Gwangyang and Yeosu as well as the local counties of Boseong and Gurae. Residents of these areas can reach these shopping stores within an hour's drive. Thus, the managers of these four stores regard residents in these areas as their valued customers and endeavor to create a differentiated image among them. In this study, 13 different images were used to determine the public's opinions and feelings towards these stores and the differences were analyzed. The store images measured overall store impression, diversity of the product, the quality of products displayed at the store, accessibility, the atmosphere, service to the customers, and so on. These images are evaluated subjectively by each customer and are major factors in them deciding to revisit the stores. The 13 images are classified into five main categories and further classified into 13 sub-categories. Three kinds of factor images were extracted from the store images in the five main categories by factor analysis using SPSS Ver. 19. The first factor image was extracted from the images of convenience, atmosphere, and service in the main categories and is called a sub-service factor for the store in this study. Accessibility to the store was classified as a convenience image in the main category and was extracted as a common factor along with diversity and the price of goods. These differences are expected according to the store location, that is, the difference between stores located in a large city and those in a small local city, and depending on the nature of survey respondents. The result shows that there is a significant difference between the stores' images with regard to accessibility, the price of products, brand image, and lighting/sound image. This study has the following limitations. First, the survey sample was restricted to residents of a small local city that includes rural and urban populations. The differences between the store images regarding traffic and accessibility are factored by store location, whether they are located within a large or a small city as well as the economic situation of these cities. Second, only the customers of large-scale stores were included in the survey as respondents. Relatively large traditional markets are held every five days in local cities and there is competition between large-scale stores and traditional markets with regard to diversity and the price of goods. It could be expected that customers in large-scale stores and customers in traditional markets would hold different store images. In future studies, images of stores in large cities should be compared with the images of stores located in small local cities. In addition, customer behavior when buying goods in large-scale stores should be compared with their behavior when buying goods in traditional markets.