1 김윤지, "북극해 해빙 탐지를 위한 Sentinel-1 HV자료의 방사보정 연구" 대한원격탐사학회 34 (34): 1273-1282, 2018
2 Nusser, S. M., "Survey methods for assessing land cover map accuracy" 10 (10): 309-331, 2003
3 Wang, L., "Sea ice concentration estimation during melt from dual-pol SAR scenes using deep convolutional neural networks : A case study" 54 (54): 4524-4533, 2016
4 Liu, H., "SVM-based sea ice classification using textural features and concentration from RADARSAT-2 dual-pol ScanSAR data" 8 (8): 1601-1613, 2014
5 Chi, J., "Prediction of arctic sea ice concentration using a fully data driven deep neural network" 9 (9): 1305-, 2017
6 Notz, D., "Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission" 354 (354): 747-750, 2016
7 Ali, I., "Methods to remove the border noise from Sentinel-1 synthetic aperture radar data: implications and importance for time-series analysis" 11 (11): 777-786, 2018
8 Stehman, S. V., "Introduction to special issue on map accuracy" 10 : 301-308, 2003
9 Mladenova, I. E., "Incidence angle normalization of radar backscatter data" 51 (51): 1791-1804, 2012
10 Cooke, C. L., "Estimating Sea Ice Concentration From SAR : Training Convolutional Neural Networks With Passive Microwave Data" 57 (57): 4735-4747, 2019
1 김윤지, "북극해 해빙 탐지를 위한 Sentinel-1 HV자료의 방사보정 연구" 대한원격탐사학회 34 (34): 1273-1282, 2018
2 Nusser, S. M., "Survey methods for assessing land cover map accuracy" 10 (10): 309-331, 2003
3 Wang, L., "Sea ice concentration estimation during melt from dual-pol SAR scenes using deep convolutional neural networks : A case study" 54 (54): 4524-4533, 2016
4 Liu, H., "SVM-based sea ice classification using textural features and concentration from RADARSAT-2 dual-pol ScanSAR data" 8 (8): 1601-1613, 2014
5 Chi, J., "Prediction of arctic sea ice concentration using a fully data driven deep neural network" 9 (9): 1305-, 2017
6 Notz, D., "Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission" 354 (354): 747-750, 2016
7 Ali, I., "Methods to remove the border noise from Sentinel-1 synthetic aperture radar data: implications and importance for time-series analysis" 11 (11): 777-786, 2018
8 Stehman, S. V., "Introduction to special issue on map accuracy" 10 : 301-308, 2003
9 Mladenova, I. E., "Incidence angle normalization of radar backscatter data" 51 (51): 1791-1804, 2012
10 Cooke, C. L., "Estimating Sea Ice Concentration From SAR : Training Convolutional Neural Networks With Passive Microwave Data" 57 (57): 4735-4747, 2019
11 Park, J. W., "Efficient thermal noise removal for Sentinel-1 TOPSAR cross-polarization channel" 56 (56): 1555-1565, 2017
12 He, K., "Deep residual learning for image recognition" 770-778, 2016
13 Ma, L., "Deep learning in remote sensing applications : A meta-analysis and review" 152 : 166-177, 2019
14 Li, Y., "Deep learning for remote sensing image classification: A survey" 8 (8): 1264-, 2018
15 Chollet, F, "Deep Learning with Python vol. 1" Manning Publications Company 2017
16 Hong, D. B., "Automatic discrimination approach of sea ice in the Arctic Ocean using Sentinel-1 Extra Wide Swath dualpolarized SAR data" 39 (39): 4469-4483, 2018
17 Parkinson, C. L., "Arctic sea ice extents, areas, and trends, 1978-1996" 104 (104): 20837-20856, 1999
18 Wulder, M. A., "An accuracy assessment framework for large-area land cover classification products derived from medium-resolution satellite data" 27 (27): 663-683, 2006
19 Inoue, J., "Additional Arctic observations improve weather and sea-ice forecasts for the Northern Sea Route" 5 : 2015