• 한국컴퓨터정보학회논문지
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• 제16권10호
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• pp.53-62
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• 2011

본 논문에서는 첨단 IT융,복합기술의 발달로 특수 기술로만 여겨졌던 영상객체인식 기술분야가 스마트-폰 기술의 발전과 더불어 개인 휴대용 단말기기로 발전하고 있다. 3D기반의 얼굴인식 검출기술은 객체인식 기술을 통하여 지능형 영상검출 인식기술기술로 진화되고 있음에 따라 영상인식을 통한 얼굴검출기술과 더불어 개발속도가 급속히 발전하고 있다. 본 논문에서는 휴먼인식기술을 기반으로 한 얼굴객체인식 영상검출을 통한 얼굴인식처리 기술의 인지 적용기술을 IP카메라에 적용하여 인가자의 입,출입등의 식별능력을 적용한 휴먼인식을 적용한 얼굴측정 기술에 대한 연구방안을 제안한다. 연구방안은 1)얼굴모델 기반의 얼굴 추적기술을 개발 적용하였고 2)개발된 알고리즘을 통하여 PC기반의 휴먼인식 측정 연구를 통한 기본적인 파라미터 값을 CPU부하에도 얼굴 추적이 가능하며 3)양안의 거리 및 응시각도를 실시간으로 추적할 수 있는 효과를 입증하였다.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Ocean and Polar Research
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• 제31권4호
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• pp.349-357
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• 2009

Ballast water is widely recognized as a serious environmental problem due to the risk of introducing non-indigenous aquatic species. In this study we aimed to investigate measures which can minimize the transfer of aquatic organisms from ballast water. Securing more reliable technologies to determine the viability of aquatic organisms is an important initiative in ballast water management systems. To evaluate the viability of marine phytoplankton, we designed the staining methods of fluorescein diacetate (FDA) and Calcein-AM assay on each target species belonging to different groups, such as bacillariphyceae, dinophyceae, raphidophyceae, chrysophyceae, haptophyceae and chlorophyceae. The FDA method, which is based on measurements of cell esterase activity using a fluorimetric stain, was the best dye for determining live cells of almost all phytoplankton species, except several diatoms tested in this study. On the other hand, although fluorescence of Calcein-AM was very clear for a comparatively longer time, green fluorescence per cell volume was lacking in most of the tested species. According to the Flow CAM method, which is a continuous imaging technique designed to characterize particles, green fluorescence values of stained cells by FDA were significantly higher than those of Calcein-AM treatments and control, implying that the Flow CAM using FDA assay could be adapted as an important tool for distinguishing living cells from dead cells. Our results suggest that the FDA and Calcein-AM methods can be adapted for use on phytoplankton, though species-specific characters are greatly different from one organism to another.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.201-205
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• 1997

With the recent advance of Web and its associated technologies, information sharing on distribute computing environments has gained a great amount of attention from many researchers in many application areas, such as medicine, engineering, and business. One basic requirement of distributed medical consultation systems is that geographically dispersed, disparate participants are allowed to exchange information readily with each other. Such software also needs to be supported on a broad range of computer platforms to increase the software's accessibility. In this paper, the development of world-wide-web based medical consultation system or radiology imaging is addressed to provide the platform independence and great accessibility. The system supports sharing of 3-dimensional objects. We use VRML (Virtual Reality Modeling Language), which is the de-facto standard in 3-D modeling on the Web. 3-D objects are reconstructed from CT or MRI volume data using a VRML format, which can be viewed and manipulated easily in Web-browsers with a VRML plug-in. A Marching cubes method is used in the transformation of scanned volume data set to polygonal surfaces of VRML. A decimation algorithm is adopted to reduce the number of meshes in the resulting VRML file. 3-D volume data are often very large-sized, and hence loading the data on PC level computers requires a significant reduction of the size of the data, while minimizing the loss of the original shape information. This is also important to decrease network delays. A prototype system has been implemented (http://netopia.snu.ac.kr/-cyber/). and several sessions of experiments are carried out.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5179-5196
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• 2019

To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제1권1호
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• pp.31-40
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• 2020

The rapid development of technologies in unmanned aerial vehicles (UAVs) has led to their use in various areas. UAVs are mainly used for commercial purposes, but their utilization is increasingly important in other areas because their operation cost is less than satellites and aerial imaging. The utilization of UAVs in the environment/ecology area is relatively new. Therefore, identifying the trends of UAV-related spatial information is significant in basic research for UAV utilization. This study quantitatively identified domestic and international research trends related to UAV utilization and analyzed research areas. An attempt was also made to identify upcoming UAV-related topics in the environment/ecology research field using text mining to analyze the bibliographic information of global research literature. Domestic UAV-related studies were classified into seven clusters where basic research on "UAV technology/industry trends" was abundant, and studies on data collection and analysis through UAV remote sensing technology have increased since 2015. Eight clusters were identified for international studies where the most active research area international was "remote sensing technology/data analysis". In addition, Canopy, Classification, Forest, Leaf Area Index, Normalized Difference Vegetation Index, Temperature, Tree, and Atmosphere appeared as the main keywords related to environment and ecology. The appearance frequencies and association strengths were high because the advancement in UAV optical sensor technology and the rapid development of image processing technology enabled the acquisition of data that could not be obtained from existing spatial information. They are recognized as future research topics as related domestic studies have begun corresponding to international research.

• 한국융합학회논문지
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• 제9권2호
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• pp.119-124
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• 2018

증강현실 기술은 사용자의 시각에 가상의 영상 정보를 결합하여 다양한 영상 정보를 동시에 취득할 수 있게 한다. 이러한 증강현실 기술은 최근 의료융합을 통해 이미지 가이드 수술(Image-Guide Operation), 수술 교육 훈련, 영상 진단 분야에서 수술 및 진단 시 환자의 장기나 조직들을 구분하여 가시화하고 가장 효과적인 수술 방법을 제시 할 수 있다. 이에 본 논문을 통해 증강현실 기술의 의료 융합을 위한 각 요소 기술의 기술적 특징과 적용 방안 등을 고찰하고자 하였다. 의료융합을 위한 증강현실 기술에서는 효율적인 의료 영상의 구현을 위해 디스플레이, 마커인식 그리고 영상합성 인터페이스 기술의 유기적인 구동이 필수적이다. 이러한 증강현실 기술은 향후, 이미지 가이드 수술, 수술 교육 및 영상 진단 등의 분야에서 현재의 의료 기술을 획기적으로 증진시킬 수 있는 방안이 될 수 있으리라 여겨진다.

• KIEAE Journal
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• 제6권2호
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• pp.67-74
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• 2006

As sustainable design technologies, advanced daylighting systems with lightshelves have been developed and are currently under monitoring the daylighting performance. This study aims to evaluate the comparative daylighting performance of sloped lightshelf and conventional glazing window with mock-up model, reconstructed as a prototype of Korean office building, sized $12.0m{\times}7.3m{\times}3.7m$ ($w{\times}d{\times}h$) and $1.8m{\times}4.8m$($w{\times}h$) for the south facing side-window was installed on the rooftop of engineering building, Kyung Hee University in Korea. It has an identical configuration of reference room and the test room. For the test room, the sloped type lightshelf system was designed as 10mm transparency sheet glass, tilt angle degree $29^{\circ}$, and total sized 1.28m (interior length 0.88m, exterior length 0.49m). It consisted of daylighting collector, entrance glazing and reflector. To assess daylighting performance, the totally 37 measuring points for illuminance and 2 view points of luminance were monitored in every 30 minutes from 12:00 to 15:00. For the detailed analysis, photometric sensors of each room were installed at work-plane (8 points), wall (7 points), ceiling (3points), and exterior horizontal illuminance (1 point). Luminance of window, rare of the room was measured under clear sky. It is to be monitored by Agilent data logger, photometric sensor Li-cor and the Radiant Imaging ProMetric 1400. Comparisons with a light factor, increase-decrease ratio, uniformity, and luminance are discussed.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2005년도 추계종합학술대회
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• pp.963-966
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• 2005

최근 급속하게 발달하고 있는 컴퓨터 네트워크와 인터넷을 기반으로 시간과 공간적인 제약에 구애받지 않고 지능적인 서비스를 수행하기 위해 유비쿼터스 컴퓨팅(Ubiquitous Computing)이 등장하였다. 이러한 유비쿼터스 컴퓨팅을 가능하게 하는 핵심 기술로 물리적 객체에 부착된 태그의 정보를 무선 주파수 식별을 통해 처리하는 RFID(Radio Frequency Identification : 무선 주파수 식별) 기술이 주목받고 있다. 현재 RFID 관련 기술들은 Auto-lD Lab과 EPCglobal Inc.을 중심으로 표준화를 위한연구가 진행 중에 있다. 그러나 현재 RFID 관련 연구는 태그와 리더에 관련된 연구들만 활발하게 진행 되고 있고, 실제 이를 서비스하기 위한 미들웨어나 소프트웨어 기술에 관한 연구는 미흡한 실정이다. 이에 본 논문에서는 Auto-lD Lab과 EPCglobal Inc.에서 제안된 EPC 네트워크 아키텍처와 기존의 어플리케이션 개발과 통합에 이용되어 왔던 개념적인 어플리케이션 아키텍처들의 특징을 비교 및 분석하였다.

• 한국산학기술학회논문지
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• 제15권2호
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• pp.1083-1088
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• 2014

최근 영상 기술과 ICT 기술의 발전으로 인해 다양한 형태의 영상처리 서비스가 가능하게 되고, 이러한 기술을 활용하는 응용 서비스가 다양화 되고 있다. 자동차 번호판 인식은 주차관리 등 차량의 정보를 인지하는 곳에 사용되는데 기존의 시스템들은 주차권 발급이나 불필요한 장비 부착 등 경제적인 단점을 갖고 있다. 이러한 문제점을 개선하기 위하여 본 논문에서는 OpenCV를 근간으로 한 emguCV를 이용하여 차량의 고유번호인 자동차 번호판 인식을 통한 자동 주차관리 시스템을 설계 및 구현하였다. 그리고 사용자 프로그램 개발에 가장 최신 기술인 WPF를 이용하여 각 주차 차량의 상세정보와 주차 시간 및 남은 주차 공간 정보 등 전체 주차관리 사항을 화면이동 없이 관리할 수 있도록 개선된 UI를 설계하였다. 본 논문에서 사용된 emguCV는 Intel 기반의 환경에서 최적화된 성능을 나타내었다. 따라서 본 논문에서는 0.5초 이내의 번호판 인식 처리 시간과 90% 이상의 인식률이라는 결과를 얻었다. 또한 관리자가 전체 시스템을 간편하고 직관적으로 관리할 수 있게 UI가 개선되었음을 보였다.