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NTIS 바로가기정보처리학회논문지. KIPS transactions on software and data engineering. 소프트웨어 및 데이터 공학, v.12 no.2, 2023년, pp.77 - 82
위성승 (숭실대학교 IT정책경영학과) , 정남수 (공주대학교 지역건설공학과) , 이원석 (농림축산식품부) , 신용태 (숭실대학교 컴퓨터공학부)
The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The ...
Statistics Korea 2010, Agricultural area Survey, 2020.
Ministry of Agriculture, Food and Rural Affairs, Press?Release, "Anyone can use the electronic map farm map?of agricultural land," 2021.
K. J. Son, "Study on applying spatial information to?agriculture based on the farm map," Journal of the Korea?Society of Informaion Technology Policy & Managment,?'21-13, Vol.13, No.1, pp.2229-2235, 2021.
Statistics Korea, "2020 Total Cultivated Land Survey using?Farm Map data," 2020.
Ministry of Agriculture, Food and Rural Affairs, "Establishment of Smart Farm Map Construction Plan," 2017.
H. K. Choi, B. K. Lee, S. R. Son, and H. H. Ahn, "CCMS?(Crop Classification Management System) detecting growth?environment changes to improve crop production rate,"?The Journal of Korea Institute of Information, Electronics,?and Communication Technology, Vol,13, No.2, pp.145-152, 2020.
J. M. Koo, "Introduction of detector analysis and large data?sets for object detection in satellite images," Korean?Society for Remote Sensing Fall Conference, 2020.
K. Kim, S. Hong, B. Choi, and E. Kim, "Probabilistic ship?detection and classification using deep learning." Applied?Sciences, Vol.8, No.6, pp.936. 2018.
Institute for Land, Infrastructure and Transport Science?and Technology Promotion, "Final report on the development of deep learning-based CCTV image retention?system for initial response to accidents in tunnels," 2019.
A. Bewley, Z. Ge, L. Ott, F. Ramos, and B. Upcroft, "Simple?online and realtime tracking," In: Proceedings of the?Image Processing (ICIP) IEEE International Conference,?pp.3464-3468, 2016.
S. H. Lee, "Land cover classification using sematic image?segmentation with deep learning," Korean Journal of?Remote Sensing, Vol.35, No.2, pp.279-288, 2019.
H. Su, S. Wei, S. Liu, J. Liang, C. Wang, J. Shi, and X. Zhang,?"HQ-ISNet: High-quality instance segmentation for remote sensing imagery," Remote Sens, Vol.12, No.6,?pp.989, 2020.
A. R. Song and Y. I. Kim, "Deep learning-based hyperspectral image classification with application to environmental geographic information systems," Korean Journal?of Remote Sensing, Vol.33, No.6, pp.1061-1073, 2017.
R. Qin, X. Huang, and A, Gruen, "Object-Based 3D building?change detection on multitemporal stereo images," IEEE,?Journal of Selected Topics in Applied Earth Observations?and Remote Sensing, Vol.8, No.5, pp.2125-2137, 2017.
C. Qi, H. Su, K. Mo, and L. J. Guibas, "Pointnet: Deep?learning on point sets for 3d classification and segmentation," In Proceedings of the IEEE Conference on Computer?Vision and Pattern Recognition, pp.652-660, 2017.
H. D. Seo and Y. M. Kim, "Object classification and change?detection in point clouds using deep learning," Journal of?Cadastre & Land InformatiX, Vol.50, No.2, pp.37-51, 2020.
K. H. Seo, C. H. Oh, D. W. Kim, M. Y. Lee, Y. J. Yang,?and Y. K. Lee, "Monitoring method of land use and land?cover change using deep learning algorithm," Sejong:?KRIHS, 2018,
K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning?for image recognition," In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,?pp.770-778. 2016.
C. N. Lim, Y. S. Park, and J. W. Lee, "Deep learning model?validation method based on image data feature coverage,"?KIPS Transactions on Software and Data Engineering,?Vol.10, No.9, pp.375-384, 2021.
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