• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.517-526
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• 2017

In this study, we analyzed the accuracy of elevation, slope, and area to the damage scale of the debris flow using the drones to track the details of the debris flow that method was between the digital topographical map(1/5,000) method and GPS ground survey method. The results are summarized as follows. At first, in the comparison of elevation, the value by the drones was 3.024m lower than the digital topography map, but in case of slope the average slope was $1.20^{\circ}$ and the maximum slope was $10.46^{\circ}$ which was higher by the drones image. Secondly, the difference area is $462m^2$ between on the digital topographic map and the drones image was calculated high, because it is determined by reflecting the uplift of the terrain as a point that calculated more accurate than the digital topographic map. Therefore, when compared with the existing method, the drone image method was very effective in terms of time and manpower.

• The Journal of Korean Society for Radiation Therapy
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• v.18 no.2
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• pp.67-73
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• 2006

Purpose: The number of patients receiving radiotherapy has increased every year and will keep increasing in the future. Therefore, the technique of radiotherapy is developing from day to day, as a result of it, the quantities of image and data used for radiotherapy are also considerably increasing. Therefore, there have been many difficulties in storing, keeping and managing them. Then, we developed and applied this system for improving complicated work process as well as solving these problems with the collaboration Medical Information Team. Materials and Methods: We exported its image at R & V (Record and Verify: Varis vision, Varian, USA) system and planning system after giving some code to be able to access from management system(RO) for department of radiation oncology to PACS. And, we programmed their information by using necessary information among many information included in DICOM head. Results: All images and data generated by our working environment (Simulation CT, L-gram image and internal body structure, DRR, does distribution )were realized at PACS and it became to be possible for clear image to be printed from any computer in department of radiation oncology. Conclusion: It was inevitable to use film during radiotherapy for patients in the past, however, due to the development of this system, film-less system became to be possible. Therefore, the darkroom space and its management cost in relation to the development process disappeared and it became to be unnecessary for spending tangible and intangible financial expense including human resources, time needed for finding film storing space and film and purchasing separate storing equipment for storing images. Finally, we think this system would be very helpful to handle ail complicated processes for radiotherapy and increasing efficiency of overall working conditions.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1013-1025
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• 2020

Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.147-155
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• 2015

The existing field survey and aerial photography involve the waste of manpower and economic loss in the coastline survey. To minimize these disadvantages, the digitization for efficient coastline extraction was conducted in this study using the points extracted from the standard coastline of the approximate highest high water and the diverse satellite images (KOMPSAT-3, SPOT-5, Landsat-8 and Quickbird-2), and the comparative accuracy analysis was conducted. The differences between the standard coastline points of the approximate highest high water and the coastline of each satellite were smallest for KOMPSAT-3, followed by Quickbird-2, SPOT-5 and Landsat-8. The significant probability from between the multipurpose applications satellite and Quickbird-2 (significant probability two-tailed) was statistically significant at 1% significance level. Therefore, high-resolution satellite images are required to efficiently extract the coastline, and KOMPSAT-3, from which images are easily acquired at a low cost, will enable the most efficient coastline extraction without external support.

• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.25-34
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• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.301-308
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• 2022

Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.103-106
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• 2013

3D LCD Module은 기존 TFT-LCD에 Parallax Barrier 방식과 Passive Glasses 방식 및 Active Glass 방식의 기술을 적합하여 만들어 진다. 현재는 3D Module 제작 후 기타 ASSY 장치를 부착 하여 시제품 출시 전에 3D 패턴을 기반으로 출하 검사를 통해 제품 이상 유무를 검사하다 보니 제품 출하 검사 시 불량 요인으로 불량 제품에 대한 모든 Repair공정을 위해 많은 시간 및 인력, 자재 등의 많은 로스 부분이 발생 하여 생산성 절감 및 제품 원가 상승의 요인이 발생 한다. 따라서 본 논문에서 제안하고자 하는 내용은 기존의 2D TFT-LCD Module 검사장비에 3D Pattern 및 동영상을 구현하여 보다 신속 하고 정확한 임베디드 환경을 이용한 2D 및 3D LCD Module용 검사 시스템을 개발 하는데 있다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1252-1256
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• 2009

Machinima is a new form of UCC(User Created Content) which utilizes 3D videogame engine technology to create animated films within virtual environments. By producing machinima content, students can get cooperative learning opportunities as well as digital storytelling skills. This case study is to introduce the educational potential of Second Life and to provide useful directions in professional curricula of digital culture content.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.40-42
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• 2013

본 논문에서는 사각 평면이 아닌 실린더나 구 형태의 비평면 스크린에 고품질 파노라마 영상을 렌더링 하기 위해 스틸 카메라를 이용한 자동 캘리브레이션과 멀티 프로젝터를 이용한 파노라마 렌더링 시스템을 제안한다. 스틸 카메라를 이용한 비평면 스크린 캘리브레이션은 특정 패턴을 스크린에 투사하고 이를 촬영하여 프로젝터의 투사 왜곡을 보정하고 멀티 프로젝터간의 중첩 영역에 대한 보정을 자동 수행한다. 캘리브레이션이 완료된 이후에 멀티 프로젝터를 이용하여 고품질의 파노라마 비디오를 렌더링 하기 위해서 본 논문에서는 복수의 멀티 시스템과 동기화 카드를 이용하여 렌더링 시스템간의 재생 동기화를 수행 하였다. 제안하는 렌더링 시스템을 적용하면 기존의 전문가의 수동작업에 의한 인력 및 보정 시간을 줄일 수 있으며, 시스템 환경이 변하더라도 쉽게 적응적으로 렌더링 환경을 구축하는 것이 가능하고 고품질의 파노라마 비디오를 렌더링 하는 것이 가능하다.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.23-40
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• 2003

6. ATC 성공사례 및 국내 현황 중앙대학교 AVID Training Center 1).사 업 명 AVID 미디어 공인 교육 센타 (AVID Tanning Center) 2003년 6월 서울 지역 유일하게 활동시작 2). 사 업 내 용 - 산업용 디지털 콘텐츠의 개발 - 생산 및 리 소스확보 - 디자인. 애니메이션. 영화. 게임 등 콘텐츠 제작에 필요한 다양한 디지털 이미지 음향등 산업용 콘텐츠를 산학협력에 의해 확보 - 공동활용체계 구축으로 디지털 콘텐츠 산업의 경쟁력 강화 - 디지털 콘텐츠 유통 및 전문인력 양성 콘텐츠의 국내 외 유통기반 구축 - 저작권 보호 관련기술의 표준화 지원 및 기술개발 사업지원 - 디지털 영화 제작 산업디자인, 사진, 게임, 디지털 콘텐츠의 기획 -콘텐츠 제작 관련 교육을 통한 콘텐츠 제작자의 저변 확대 - 디지털 콘텐츠 분양 정보 공동체 조성 - 디지털 콘텐츠 경영정보, 마케팅 정보의 공유 - 디지털 콘텐츠 산업 통계 및 지표 연구, 지역별 특성 연구 지원 - 디지털 콘텐츠 산업 관련 정보 네트워크 구축 제공