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Yoo, S.H., J.S., Lee, J.S., Bae. And H.G. Sohn, 2020. Automatic Generation of Land Cover Map Using Residual U-Net, Journal of the Korean Society of Civil Engineers, 40(5): 535-546 (in Korean with English abstract).
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Lee H.S. and K.S. Lee, 2017. Effect of Red-edge Band to Estimate Leaf Area Index in Close Canopy Forest, Korean Journal of Remote Sensing, 33(5-1): 571-585 (in Korean with English abstract).
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3 |
Zhang, Z., Q. Liu, and Y. Wang, 2018. Road extraction by deep residual u-net, IEEE Geoscience and Remote Sensing Letters, 15(5): 749-753.
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Kim, S.H., H.Y. Kong, and T.K. Kim, 2015. Development and application of the assessment method of no net loss of greenness for urban ecosystem health improvement, Ecology and Resilient Infrastructure, 2(4): 311-316 (in Korean with English abstract).
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5 |
Eom, D.Y., 2017. 3D Reality Model Generation Technique of Spatial Objects by Unmanned Aerial Photogrammetry, Broadcasting and Media Magazine, 22(2): 44-52 (in Korean with English abstract).
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Goodfellow, I., Y. Bengio, and A. Courville, 2016. Deep Learning, MIT Press, Cambridge, MA, USA.
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Jeon, E.I., S.H. Kim, B.S. Kim, K.H. Park and O.I. Choi, 2020. Semantic Segmentation of Drone Imagery Using Deep Learning for Seagrass Habitat Monitoring, Korean Journal of Remote Sensing, 36(2-1): 199-215 (in Korean with English abstract).
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Jo, Y.W., S.B. Lee, Y.J. Lee, H.G. Kahng, S.H. Park, S.H. Bae, M.K. Kim, S.W. Han, and S.B. Kim., 2021. Semantic Segmentation of Cabbage in the South Korea Highlands with Images by Unmanned Aerial Vehicles, Applied Sciences, 11(10): 4493.
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Kim, J., Y. Song, and W.K. Lee, 2021. Accuracy analysis of Multi-series Phenological Landcover Classification Using U-Net-based Deep Learning Model - Focusing on the Seoul, Republic of Korea -, Korean Journal of Remote Sensing, 37(3): 409-418 (in Korean with English abstract).
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Agisoft, 2021. Agisoft Metashape, https://www.agisoft.com/, Accessed on Jun. 22, 2021.
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Seong, S.J., W.J. Park, Y.T. Lee, and J.W. Cha, 2021. Dynamic Sampling Scheduler for Unbalanced Data Classification, Proc. of Annual Conference on Human and Language 2021, Technology, https://sites.google.com/view/hclt2021, Oct. 14-15, pp. 221-226.
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Ban, H.Y., J.K. Baek, W.G. Sang, J.H. Kim, and M.C. Seo, 2021. Estimation of the Lodging Area in Rice Using Deep Learning, The Korean Journal of Crop Science, 66(2): 105-111 (in Korean with English abstract).
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Choi, S.K., S.K. Lee, Y.B. Kang, D.Y. Choi, and J.W. Choi, 2020. Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Classification Upland Crop in Small Scale Agricultural Land, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography, 38(6): 671-679 (in Korean with English abstract).
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Lee, H.Y., 2000. Korea Climate, Beopmunsa, Seoul, KOR.
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Lee J.O. and S.M. Sung, 2019. Quality Evaluation of UAV Images Using Resolution Target, Journal of the Korean Association of Geographic Information Studies, 22(1): 103-113 (in Korean with English abstract).
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Lee, Y.C., 2018. Vegetation Monitoring using Unmanned Aerial System based Visible, Near Infrared and Thermal Images, Journal of Cadastre and Land InformatiX, 48(1): 71-91 (in Korean with English abstract).
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Kim, T.W., D.J. Choi, G.J. Wee, and Y.C. Suh, 2013. Detection of Small Green Space in an Urban Area Using Airborne Hyperspectral Imagery and Spectral Angle Mapper, Journal of the Korean Association of Geographic Information Studies, 16(2): 88-100 (in Korean with English abstract).
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Li, G., W.T. Han, S.J. Huang, W.T. Ma, Q. Ma, and X. Cui, 2021. Extraction of Sunflower Lodging Information Based on UAV Multi-Spectral Remote Sensing and Deep Learning, Remote Sensing, 13(14): 2721.
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Moon, C.S., J.Y. Shim, S.B. Kim, and S.Y. Lee, 2010. A Study on the Calculation Methods on the Ratio of Green Coverage Using Satellite Images and Land Cover Maps, Journal of Korean Society of Rural Planning, 16(4): 53-60 (in Korean with English abstract).
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Song, A.R. and Y.I. Kim, 2017. Deep Learning-based Hyperspectral Image Classification with Application to Environmental Geographic Information Systems, Korean Journal of Remote Sensing, 33(6-2): 1061-1073 (in Korean with English abstract).
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