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Synergistic Use of Sentinel-1 and Sentinel-2 Images for in-Season Crop Type Classification Using Google Earth Engine and Machine Learning.

, , , , and . IGARSS, page 3498-3501. IEEE, (2023)

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Assimilation of Deep Learning and Machine Learning Schemes into a Remote Sensing-Incorporated Crop Model to Simulate Barley and Wheat Productivities., , , , , and . Remote. Sens., 14 (21): 5443 (2022)Synergistic Use of Sentinel-1 and Sentinel-2 Images for in-Season Crop Type Classification Using Google Earth Engine and Machine Learning., , , , and . IGARSS, page 3498-3501. IEEE, (2023)Mathematical Integration of Remotely-Sensed Information into a Crop Modelling Process for Mapping Crop Productivity., , , , and . Remote. Sens., 11 (18): 2131 (2019)Nationwide Projection of Rice Yield Using a Crop Model Integrated with Geostationary Satellite Imagery: A Case Study in South Korea., , and . Remote Sensing, 10 (10): 1665 (2018)Estimation of evapotranspiration over northeast Asia using modis products and MM5 FDDA data., , , , , and . IGARSS, page 2087-2090. IEEE, (2010)Estimation of the Hourly Aerosol Optical Depth From GOCI Geostationary Satellite Data: Deep Neural Network, Machine Learning, and Physical Models., , , , , and . IEEE Trans. Geosci. Remote. Sens., (2022)Smartwatch Strap Wireless Power Transfer System With Flexible PCB Coil and Shielding Material., , , , , , , , and . IEEE Trans. Ind. Electron., 66 (5): 4054-4064 (2019)High Resolution Land Application Approach Using Micosatellite Costellation(NEONSAT) in Korea., , , , , and . IGARSS, page 7168-7170. IEEE, (2024)