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NTIS 바로가기대한원격탐사학회지 = Korean journal of remote sensing, v.36 no.5 pt.1, 2020년, pp.823 - 833
성선경 (충북대학교 토목공학과) , 나상일 (농촌진흥청 국립농업과학원 기후변화평가과) , 최재완 (충북대학교 토목공학과)
In order to stably produce crops, there is an increasing demand for effective crop monitoring techniques in domestic agricultural areas. In this manuscript, a cultivation area extraction method by using deep learning model is developed, and then, applied to satellite imagery. Training dataset for cr...
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Bernstein, L. S., X. Jin, B. Gregor, and S. M. Adler-Golden, 2012. Quick atmospheric correction code: algorithm description and recent upgrades, Optical Engineering, 51(11): 111719-1.
Huang, G., Z. Liu, L. Van Der Maaten, and K.Q. Weinberger, 2017. Densely connected convolutional networks, Proc. of the IEEE conference on computer vision and pattern recognition, Honolulu, Hawaii, Jul. 21-26, pp. 4700-4708.
Jegou, S., M. Drozdzal, D. Vazquez, A. Romero, and Y. Bengio, 2017. The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation, Proc. of 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, Hawaii, Jul. 21-26, pp. 1175-1183.
Ji, S., C. Zhang, A. Xu, Y. Shi, and Y. Duan, 2018. 3D convolutional neural networks for crop classification with multi-temporal remote sensing images, Remote Sensing, 10(1): 75.
Kang, W., Y. Xiang, F. Wang, and H. You, 2019. EU-Net: An efficient fully convolutional network for building extraction from optical remote sensing images, Remote Sensing, 11(23): 2813.
Lee, S.H., Y.G. Park, N.Y. Park, S.H. Lee, and J.Y. Choi, 2014. Extraction of paddy field Jaeryeong, North Korea by object-oriented classification with RapidEye NDVI imagery, Journal of the Korean Society of Agricultural Engineers, 56(3): 55-64. (in Korean with English abstract).
Mazzia, V., A. Khaliq, and M. Chiaberge, 2020. Improvement in land cover and crop classification based on temporal features learning from Sentinel-2 data using recurrent-convolutional neural network (R-CNN), Applied Sciences, 10(1): 238.
Yoo. H., K. Lee, S. Na, C. Park, and N. Park, 2017. Field crop classification using multi-temporal high-resolution satellite imagery: A case study garlic/onion field, Korean Journal of Remote Sensing, 33(5-2): 621-630 (in Korean with English abstract).
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