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Comparison of Machine Learning Methods Applied to SAR Images for Forest Classification in Mediterranean Areas.

, , , , , and . Remote. Sens., 12 (3): 369 (2020)

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Early-Season Crop Mapping on an Agricultural Area in Italy Using X-Band Dual-Polarization SAR Satellite Data and Convolutional Neural Networks., , , , , , , , , and 1 other author(s). IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2022)Remote Sensing of Forest Biomass Using GNSS Reflectometry., , , , , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2020)In-Season Mapping of Crop Type with Optical and X-Band SAR Data: A Classification Tree Approach Using Synoptic Seasonal Features., , , , and . Remote. Sens., 7 (10): 12859-12886 (2015)Monitoring of snow cover on Italian Alps using AMSR-E and Artificial Neural Networks., , , and . IGARSS, page 1572-1575. IEEE, (2012)Forest Biomass Estimate on Local and Global Scales Through GNSS Reflectometry Techniques., , , , , , and . IGARSS, page 8680-8683. IEEE, (2019)Integration of multi-seasonal Landsat 8 and TerraSAR-X data for urban mapping: An assessment., , and . JURSE, page 1-4. IEEE, (2015)Evaluation of vegetation effect on the retrieval of snow parameters from backscattering measurements: A contribution to CoReH2O mission., , , , , and . IGARSS, page 1772-1775. IEEE, (2010)Airborne GNSS-R Polarimetric Measurements for Soil Moisture and Above-Ground Biomass Estimation., , , , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 7 (5): 1522-1532 (2014)Mapping Woody Volume of Mediterranean Forests by Using SAR and Machine Learning: A Case Study in Central Italy., , , , , , , and . Remote. Sens., 13 (4): 809 (2021)A Multi-Stage model based on YOLOv3 for defect detection in PV panels based on IR and Visible Imaging by Unmanned Aerial Vehicle., , , and . CoRR, (2021)