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Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables.

, , , , , , , , , , , , and . Remote Sensing, 11 (19): 2270 (2019)

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Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards., , , , , , , , , and . CoRR, (2017)Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area., , and . Int. J. Applied Earth Observation and Geoinformation, (2013)Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables., , , , , , , , , and 3 other author(s). Remote Sensing, 11 (19): 2270 (2019)A Single LED Multi-reception Indoor Visible Light Position System Based on Power Estimation-Angle Algorithm., , , and . ISPACS, page 363-367. IEEE, (2018)Leaf and canopy water content estimation in cotton using hyperspectral indices and radiative transfer models., , , and . Int. J. Applied Earth Observation and Geoinformation, (2014)Comparability of Red/Near-Infrared Reflectance and NDVI Based on the Spectral Response Function between MODIS and 30 Other Satellite Sensors Using Rice Canopy Spectra., , , , and . Sensors, 13 (12): 16023-16050 (2013)Grounded Language Learning in a Simulated 3D World., , , , , , , , , and 4 other author(s). CoRR, (2017)Latent Predictor Networks for Code Generation., , , , , , and . ACL (1), The Association for Computer Linguistics, (2016)Monitoring nitrogen concentration of oilseed rape from hyperspectral data using radial basis function., , , , , and . Int. J. Digital Earth, 6 (6): 550-562 (2013)Retrieval Of Pigment Contents In Rice Leaves And Panicles Using Hyperspectral Data By Artificial Neuron Network Models., , and . IGARSS, page 1416-1419. IEEE, (2005)