• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 Techno-Fair 및 추계학술대회 논문집 전기물성,응용부문
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• pp.140-141
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• 2007

본 연구에서는 고분해능 및 고감도화된 시스템 개발을 위하여 AOTF를 이용하여 하이퍼스펙트럼 영상기법을 활용한 전임상 영상장비에 대한 연구를 수행하였다. 제작된 고감도 하이퍼스펙트럼 분자영상 시스템의 생물학적 적용을 위하여, AOTF의 파장 또는 진동수를 변화시키면서 GFP가 발현된 HEK 293 세포의 이미지를 촬영하였다. 또한, 제작된 실험 대상물 이미지화 시스템을 이용해서 실험용 쥐의 이미지를 촬영하였다. 실험용 쥐를 크세논 아크램프 사용 전 후 이미지를 촬영한 결과 크세논 아크 램프 사용 후에는 청색의 선명한 영상을 얻을 수 있었다.

• 한국광학회:학술대회논문집
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• 한국광학회 2009년도 동계학술발표회 논문집
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• pp.217-218
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• 2009

• 스마트미디어저널
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• 제13권8호
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• pp.39-48
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• 2024

최근 초분광 영상을 활용하여 작물의 생육 분석 및 질병을 조기에 진단하는 다양한 연구들이 등장하였지만, 수많은 스팩트럼 밴드를 사용하거나 최적의 밴드를 탐색하는 것은 어려운 문제로 남아 있다. 본 논문에서는 초분광 영상을 이용한 딥러닝 기반의 최적화된 작물 영역 스펙트럼 밴드를 탐색하는 방법을 제안한다. 제안한 방법은 초분광 영상 내 RGB 영상을 추출하여 Vision Transformer 기반 Segformer을 통해 배경과 전경 영역을 분할한다. 분할된 결과는 그레이스케일 전환한 초분광 영상 각 밴드에 투영 후 전경과 배경 영역의 평균 픽셀 비교를 통해 작물 영역의 최적화된 스펙트럼 밴드를 탐색한다. 제안된 방법을 통해 전경과 배경 분할 성능은 평균 정확도 98.47%와 mIoU 96.48%의 성능을 나타내었다. 또한, mRMR 방법에 비해 제안 방법이 작물 영역 밀접하게 연관된 NIR 영역에 수렴하는 것을 확인하였다.

• 한국재난정보학회 논문집
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• 제6권2호
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• pp.87-106
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• 2010

This research focused on the effect of the GIS, uIT, and RS based smart disaster systems. Ubiquitous IT strongly involved in intelligent analysis for the natural disasters. Remote sensing technologies, such as hyper-spectral imaging, MODIS, LiDAR, Radar, and optical imaging processes, can contribute many means of investigation for the natural and unnatural problems in the atmosphere, hydrosphere, and lithosphere. Recent IT trends guides abundant smart solutions, such as automatic sensing using USN, RFID, and wireless communication devices. Smart monitoring systems using intelligent LBSs will produce many ways of checking, processes, and controls for the human safeties. In results, u-smart GIS, uIT, and RS based disaster systems must be using ubiquitous IT involved smart systems using intelligent GIS methods.

• 천문학회지
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• 제43권2호
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• pp.41-54
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• 2010

We report relative proper motion measurements of $H_{2}O$ masers in massive star-forming region W51 Main, based on data sets of VLBI observations for $H_{2}O$ masers at 22 GHz with Japanese VERA telescopes from 2003 to 2006. Data reductions and single-beam imaging analysis are to measure internal kinematics of maser spots and eventually to estimate the three-dimensional kinematics of $H_{2}O$ masers in W51 Main. Average space motions and proper motion measurements of $H_{2}O$ masers are given both graphical and in table formats. We find in this study that W51 Main appears to be associated with hyper-compact H II region with multiple massive proto-stars whose spectral types are of late O.

• 한국군사과학기술학회지
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• 제22권4호
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• pp.484-491
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• 2019

General Hyperspectral Image Sensor acquires an image of line form such as a thin rectangle shape because of using 1D array Push Broom or Whisk Broom scanning method. A special mechanism is required for a Hyperspectral Image Sensor to operate for nadir and slant range. To design the mechanism, the characteristics of the flight motion and the overlap rate between consecutive frames were analyzed. Also, system requirements were proposed through modeling and simulation.

• 농업과학연구
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• 제47권3호
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• pp.633-644
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• 2020

Rice paper is an element of Vietnamese cuisine that can be used to wrap vegetables and meat. Rice and starch are the main ingredients of rice paper and their mixing ratio is important for quality control. In a commercial factory, assessment of food safety and quantitative supply is a challenging issue. A rapid and non-destructive monitoring system is therefore necessary in commercial production systems to ensure the food safety of rice and starch flour for the rice paper wrap. In this study, fluorescence hyperspectral imaging technology was applied to classify grain flours. Using the 3D hyper cube of fluorescence hyperspectral imaging (fHSI, 420 - 730 nm), spectral and spatial data and chemometric methods were applied to detect and classify flours. Eight flours (rice: 4, starch: 4) were prepared and hyperspectral images were acquired in a 5 (L) × 5 (W) × 1.5 (H) cm container. Linear discriminant analysis (LDA), partial least square discriminant analysis (PLSDA), support vector machine (SVM), classification and regression tree (CART), and random forest (RF) with a few preprocessing methods (multivariate scatter correction [MSC], 1^st and 2^nd derivative and moving average) were applied to classify grain flours and the accuracy was compared using a confusion matrix (accuracy and kappa coefficient). LDA with moving average showed the highest accuracy at A = 0.9362 (K = 0.9270). 1D convolutional neural network (CNN) demonstrated a classification result of A = 0.94 and showed improved classification results between mimyeon flour (MF)1 and MF2 of 0.72 and 0.87, respectively. In this study, the potential of non-destructive detection and classification of grain flours using fHSI technology and machine learning methods was demonstrated.

• 응용통계연구
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• 제29권5호
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• pp.859-872
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• 2016

초분광 영상 데이터는 픽셀마다 수백 개의 스펙트럼 밴드에 대한 정보가 주어지는 고차원 데이터로, 농업, 식품처리, 광물학, 물리학, 환경학, 지리학 등 광범위한 분야에 활용되고 있다. 그 중 하나는 토지 피복의 분류 문제인데, 이는 자연 재해 예방, 자연 자원 감시, 환경에 대한 정보 수집에 있어서 중요한 문제이다. 하지만 차원의 저주, 시공간적 변동성, 레이블된 데이터의 부족 때문에 토지 피복의 정확한 분류에는 어려움이 따른다. 이 논문에서는 이러한 문제를 해결하기 위해 컨볼루션 신경망에 기반한 새로운 심층 학습 구조를 제안한다. 제안된 구조는 원하는 지점 주변 픽셀의 정보를 컨볼루션 신경망을 통해 처리하고, 그 지점의 스펙트럼 정보를 강조하기 위해 컨볼루션 층의 출력과 스펙트럼 정보를 함께 소프트맥스 분류기의 입력으로 사용한다. 이 구조는 추가적인 특징 추출 과정을 필요로 하지 않고, 그래픽 처리 장치 등을 이용한 병렬화가 간편하다는 점에서 기존 방법들보다 유리하다. 실험 결과, 제안된 구조는 기존에 가장 좋은 성능을 보인 분류기와 비슷하거나 더 좋은 분류 정확도를 보여 좋은 일반화 성능을 보이는 것을 확인할 수 있었다.

• 항공우주산업기술동향
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• 제6권1호
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• pp.124-134
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• 2008

The rising demand for the high efficiency and high covertness in UAV motivates the miniature design of the high performing mission sensors, or payloads. One of the promising payload sensors, EO/IR sensor has evolved satisfying its demands and became the main stand-alone mission sensor for 200kg-range UAV. One aspect in development of EO/IR sensor concerns lack of specification criterions to represent its performance. Even though the high demand and competition among each manufacturer caused EO/IR features subject to rapid change collateral to new technology, the datasheets maintained the conventional outdated formats which leave some of the major components in ambiguity. Making comparisons or predicting actual performance with such datasheets is hardly worthwhile; yet, they could be important reference guide for the potential customers what to expect for the upcoming EO/IR. According to UAS Roadmap 2007-2032 published by DoD, one of the main potential customers as well as a main investor of EO/IR technology, EO/IR is expected to play key roll in solving urgent problems, such as see and avoid system. This paper will examine the recent representative EO/IR specialized in UAS missions through datasheets to find out current trend and eventually extrapolate the possible future trend.

• 한국가시화정보학회지
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• 제21권1호
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• pp.103-109
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• 2023

This research developed a measurement technique that can measure the oxygen temperature inside a high temperature furnace. Instead of measuring only changes in frequency components within a small range used in the existing variable laser absorption spectroscopy, laser spectroscopy technology was used to spread out wavelength of the light source passing through the gas Based on a total of 20,000 image data, research was conducted to predict the temperature of a high-temperature furnace using CNN with black and white images in the form of spectral bands by temperature of 25 to 800 degrees. The optimal model was found through Hyper parameter optimization, R2 score is 0.89, and the accuracy of the test data is 88.73%. Based on this research, it is expected that concentration measurement and air-fuel ratio control technology can be applied.