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Function Modeling Improves the Efficiency of Spatial Modeling Using Big Data from Remote Sensing., и . Big Data Cogn. Comput., 1 (1): 3 (2017)New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas., , и . ISPRS Int. J. Geo Inf., 7 (4): 156 (2018)Fine Resolution Probabilistic Land Cover Classification of Landscapes in the Southeastern United States., , , , и . ISPRS Int. J. Geo Inf., 7 (3): 107 (2018)Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications., , , , , , , , , и 51 other автор(ы). Big Data, 1 (4): 196-201 (2013)Aligning implicit learning and statistical learning: Two approaches, one phenomenon., , , , , и . CogSci, cognitivesciencesociety.org, (2016)Beyond protein expression, MOPED goes multi-omics., , , , , , , , , и 1 other автор(ы). Nucleic Acids Res., 43 (Database-Issue): 1145-1151 (2015)Mapping Forest Characteristics at Fine Resolution across Large Landscapes of the Southeastern United States Using NAIP Imagery and FIA Field Plot Data., , , , и . ISPRS Int. J. Geo Inf., 7 (4): 140 (2018)Using Forest Inventory Data with Landsat 8 Imagery to Map Longleaf Pine Forest Characteristics in Georgia, USA., , , и . Remote Sensing, 11 (15): 1803 (2019)Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging., , , , , , , , и . NeuroImage, (2016)