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Analysis of Image Preprocessing Effects in a Landsat Image Simulation
서대교,어양담,백근우 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.7
Optical remote sensing has limitations in obtaining images due to weather and environmental effects, so these limitations must be overcome to produce time-series image data. As an alternative to this, research are being conducted to simulate images at a specific time for which a specific image is needed. The purpose of this study is to improve the results of this process by preprocessing the input images of a multiple linear regression model alongside other remote sensing image simulation methods. Specifically, the input images, which are applied to a multi-linear regression equation, are preprocessed for phenological and radiometric normalization by a random forest regression model. The experimental results show that the proposed method is superior to the conventional methods both visually and quantitatively.
Regulation of Transcription from Two ssrS Promoters in 6S RNA Biogenesis
이지영,이영훈,박홍만,백근우,김광선 한국분자세포생물학회 2013 Molecules and cells Vol.36 No.3
ssrS-encoded 6S RNA is an abundant noncoding RNA that binds σ70-RNA polymerase and regulates expression at a subset of promoters in Escherichia coli. It is tran-scribed from two tandem promoters, ssrS P1 and ssrS P2. Regulation of transcription from two ssrS promoters in 6S RNA biogenesis was examined. Both P1 and P2 were growth phase-dependently regulated. Depletion of 6S RNA had no effect on growth-phase-dependent transcription from either promoter, whereas overexpression of 6S RNA increased P1 transcription and decreased P2 transcription, suggesting that transcription from P1 and P2 is subject to feedback activation and feedback inhibition, respectively. This feedback regulation disappeared in Δfis strains, supporting involvement of Fis in this process. The differential feedback regulation may provide a means for maintaining appropriate cellular concentrations of 6S RNA.
김혜진(Kim, Hye Jin),어양담(Eo, Yang Dam),서대교(Seo, Dae Kyo),백근우(Paik, Geun Woo) 한국측량학회 2019 한국측량학회 학술대회자료집 Vol.2019 No.4
본 연구에서는 딥러닝 기법 중 다층 퍼셉트론을 활용하여 흑백 항공사진을 자동으로 채색한다. 제안한 방법은 입력 영상과 시기가 다른 동일 지역의 컬러 항공사진 참조하여 미 변화 지역을 추출하고 다층 퍼셉트론을 통해 색 공간정보를 학습시켜 컬러를 예측한다. 사실적인 채색을 위하여 색 공간정보뿐만 아니라 가버 필터를 활용한다. 실험 결과, 좋은 성능의 흑백사진의 컬러 복원이 가능함을 확인하였다.