• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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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.

• 천문학회보
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• 제45권1호
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• pp.65.1-65.1
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• 2020

We present high-resolution, high-sensitivity continuum data of NGC 4522 observed at 3 cm (X-band) and 10 cm (S-band) in full polarization mode using the JVLA. This observation has 2 - 4 times better spatial resolution and 2 - 5 times better sensitivity compared to previous continuum observations. NGC 4522 is a Virgo spiral galaxy undergoing active ram pressure stripping. This galaxy is particularly well known for the CO emission detected outside its stellar disk, some of which coincides with the extraplanar HI gas and Halpha patches. The major goal of our JVLA observation is to leverage our understanding of the influence of the ram pressure on the general ISM field and multi-phase medium. By combining our new deep radio continuum data and previous observations, we will investigate how the B-field properties can be affected by the ram pressure, and what roles the B-field plays in the stripping process of the multi-phased ISM and in the star formation activity when the ram pressure is present.

• 대한원격탐사학회지
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• 제28권6호
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• pp.683-691
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• 2012

High resolution satellite images are now widely used for a variety of mapping applications including photogrammetry, GIS data acquisition and visualization. As the spectral and spatial data size of satellite images increases, a greater processing power is needed to process the images. The solution of these problems is parallel systems. Parallel processing techniques have been developed for improving the performance of image processing along with the development of the computational power. However, conventional CPU-based parallel computing is often not good enough for the demand for computational speed to process the images. The GPU is a good candidate to achieve this goal. Recently GPUs are used in the field of highly complex processing including many loop operations such as mathematical transforms, ray tracing. In this study we proposed a technique for parallel processing of high resolution satellite images using GPU. We implemented a spectral radiometric processing algorithm on Landsat-7 ETM+ imagery using CUDA, a parallel computing architecture developed by NVIDIA for GPU. Also performance of the algorithm on GPU and CPU is compared.

• 한국지구과학회지
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• 제45권3호
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• pp.192-202
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• 2024

해양재분석 자료는 관측 자료를 수치 모델에 동화함으로, 관측 자료의 시공간적인 제약을 극복하고 해양 변수 간의 물리적 상호작용을 고려한 격자화된 고해상도 정보를 제공함으로써 해양순환 및 기후 연구에 광범위하게 사용되고 있다. 이 연구에서는 기존에 생산된 12년간(2011년부터 2022년까지)의 북서태평양 지역해양 재분석 자료를 확장하여 30년간(1993년부터 2022년까지)의 1/24° 수평해상도를 갖는 장기 재분석 자료(K-ORA22E)를 생산하고, 이를 분석하여 한반도 주변해역에서의 장기 해양기후변화를 진단하였다. K-ORA22E 데이터를 통해 한반도 주변 해역의 수온 상승 경향을 분석한 결과, 쿠로시오 확장역에서 쿠로시오의 경로가 지난 30년 동안 1년에 약 6 km 씩 북상하였으며, 쿠로시오 경로의 북쪽에서 수온 상승이 두드러졌다. 한반도 주변 해역 중에서는 동해에서 수온 상승이 가장 뚜렷했다. 특히, 동해에서는 표층보다는 중층에서 수온 상승이 두드러졌으며, 동한난류의 수온 상승률은 전 지구 평균보다 2-3배 높았다. 황해저층냉수가 출현하는 황해 중앙부에서는 장기적으로 수온이 상승하였으나, 한반도 서해안과 남해안에서는 수온이 오히려 감소하는 경향이 나타났다. 이러한 수온의 장기변화의 공간적인 차이는 쿠로시오 해류의 북상에 따른 열수송의 경로와 밀접한 관련이 있을 것으로 보인다. 이 연구에서 구축된 K-ORA22E와 같은 고해상도 지역 해양 재분석 자료는 한반도 주변 해역의 장기 변동성을 이해하고 기후 변화의 영향을 분석하는 데 중요한 기초 자료로 활용될 수 있을 것이다.

• 한국측량학회지
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• 제36권3호
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• pp.135-152
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• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

• 대한원격탐사학회지
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• 제23권3호
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• pp.161-169
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• 2007

A study was conducted in the Hong Kong with the aim of deriving an algorithm for the retrieval of suspended sediment (SS) and sea surface salinity (SSS) concentrations from Aqua/MODIS level 1B reflectance data with 250m and 500m spatial resolutions. 'In-situ' measurements of SS and SSS were also compared with coincident MODIS spectral reflectance measurements over the ocean surface. This is the first study of SSS modeling in Southeast Asia using earth observation satellite images. Three analysis techniques such as multiple regression, linear regression, and principal component analysis (PCA) were performed on the MODIS data and the 'in-situ' measurement datasets of the SS and SSS. Correlation coefficients by each analysis method shows that the best correlation results are multiple regression from the 500m spatial resolution MODIS images, $R^2$= 0.82 for SS and $R^2$ = 0.81 for SSS. The Root Mean Square Error (RMSE) between satellite and 'in-situ' data are 0.92mg/L for SS and 1.63psu for SSS, respectively. These suggest that 500m spatial resolution MODIS data are suitable for water quality modeling in the study area. Furthermore, the application of these models to MODIS images of the Hong Kong and Pearl River Delta (PRO) Region are able to accurately reproduce the spatial distribution map of the high turbidity with realistic SS concentrations.

• 대한원격탐사학회지
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• 제2권2호
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• pp.79-94
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• 1986

TM data, which have better resolution in spatial and spectral than MSS data, were used for this study, and several Image Processing Techniques (IPT) were examined for finding the best IPT to fit to lineament extraction and mineralized zone mapping. The Ryeongnam area was selected as test area, because the area is one of major mineralized zones in Korea and its hydrothermal alteration zone is wider and deeper than other areas. The spatial filtering method is most optimum one for limeament extraction: that is, the directional spatial filtering is most efficient to detect N-S, E-W direction lineaments on the image, and the high boost filtering can be applied for mapping all direction lineaments. The ratio method was selected for detecting altered zone. It is possible to make several tens combinations in ratio with 7 bands of TM data, but considering spectral characteristics of each band of TM to the geological meterials and vegetation, the band 4/band 3(A), band 5/band 7(B), and B/A ratio methods were chosen among them. The 5/7 ratio image did not show clearly the altered area due to noise from vegetation cover, so the 4/3 ratio imae was used for trying to decrease the effect of vegetation. As a result the B/A ratio image showed quite nicely the altered zone of the test area. In conclusion, the spatial filtering is the best image processing techniques for lineament mapping, and the B/A ratio image in TM data is useful for the mineralized zone mapping.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제14권7호
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• pp.748-752
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• 2008

위성영상 촬영 기법의 발전과 인터넷 인프라의 확충으로 인해 이를 활용하는 다양한 서비스가 이루어지고 있지만, 대부분 저해상도의 위성영상과 수치고도모형 데이타를 기반하고 있다. 본 논문은 고해상도의 위성영상 데이타를 웹 환경에서 효율적인 스트리밍 서비스가 가능하도록 원시데이타를 가공하는 모듈과 이를 전송하고 렌더링하는 모듈을 구현하였다. 실제 북한산 일대의 위성사진 데이터를 대상으로 논문에서 제안된 기법을 활용하였으며, 넓은 외부지형을 실시간 처리할 때 발생하는 그래픽 문제를 효율적으로 해결하고 있음을 보인다.

• 대한원격탐사학회지
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• 제12권1호
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• pp.60-80
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• 1996

AVHRR(Advanced Very High Resolution Radiometer) on NOAA satellite provides data in five spectral, one in visible range, one in near infrared and three in thermal range. In this paper, application of NOAA/AVHRR data is studied for environment monitoring such as cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index, forest fire, flood, snow cover and so on. The analyses for cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index and forest fire showed reasonable agreement. But monitoring for flood and snow cover was uneasy due to the limitations such as cloud contamination, low spatial resolution. So this research had only simple purpose to identify well-defined waterbody for dynamic monitoring of flood. Based on development of these basic algorithms, we have a plan to further reseach for environment monitoring using AVHRR data.

• 응용통계연구
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• 제35권1호
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• pp.161-175
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• 2022

뇌활동으로 발생하는 전기신호는 다시 자기신호로 유도되는데 센서로 측정한 것을 뇌자도(magnetoencephalography, MEG)라고 한다. MEG 기술은 비접촉, 비침습적인 측정방법이고 시간분해능과 공간분해능력이이 우수하기 때문에 뇌의 기능적인 정보를 얻는데 유용하게 사용될 수 있다. 또한 MEG 신호를 측정하고 분석하여 뇌신경전류의 활동을 이해할 수 있고 나아가 정밀한 뇌기능 연구가 가능하다. 본 연구에서는 뇌 활동(brain activity) 현상에 관한 궁극적 정보를 얻기위해 MEG 데이터의 특성을 설명하고 통계적 문제를 다루어 앞으로 뇌연구에 통계학의 필요성과 뇌정보학의 중요성을 강조하고자 한다.