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Table representation of search results timeline featuring number of search results per year.
Year | Number of Results |
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2018 | 1 |
2019 | 1 |
2021 | 1 |
2022 | 2 |
2024 | 0 |
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Incorporation of machine learning and deep neural network approaches into a remote sensing-integrated crop model for the simulation of rice growth.
Sci Rep. 2022 May 30;12(1):9030. doi: 10.1038/s41598-022-13232-y.
Sci Rep. 2022.
PMID: 35637314
Free PMC article.
Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea.
Jeong S, Ko J, Yeom JM.
Jeong S, et al. Among authors: yeom jm.
Sci Total Environ. 2022 Jan 1;802:149726. doi: 10.1016/j.scitotenv.2021.149726. Epub 2021 Aug 19.
Sci Total Environ. 2022.
PMID: 34464811
Free article.
Item in Clipboard
Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Using Data Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea.
Yeom JM, Park S, Chae T, Kim JY, Lee CS.
Yeom JM, et al.
Sensors (Basel). 2019 May 5;19(9):2082. doi: 10.3390/s19092082.
Sensors (Basel). 2019.
PMID: 31060305
Free PMC article.
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Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model.
Yeom JM, Jeong S, Jeong G, Ng CT, Deo RC, Ko J.
Yeom JM, et al.
Sci Rep. 2018 Oct 31;8(1):16121. doi: 10.1038/s41598-018-34550-0.
Sci Rep. 2018.
PMID: 30382152
Free PMC article.
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