Using deep learning for multivariate mapping of soil with quantified uncertainty

References

Page 1

	Year	Citations
R: A Language and Environment for Statistical Computing R Core Team	2000	352.8K
Advances in Neural Information Processing Systems 29 Onur Teymur, Kostas Zygalakis, Ben Calderhead EngineeringComputational NeuroscienceComputer ScienceIntelligent SystemsNeuromorphic Engineering	2016	13.4K
Backpropagation Applied to Handwritten Zip Code Recognition Yann LeCun, Bernhard E. Boser, J. S. Denker, Neural Computation Artificial IntelligenceConvolutional Neural NetworkEngineeringMachine LearningAi Foundation	1989	11.6K
High-Resolution Global Maps of 21st-Century Forest Cover Change Matthew C. Hansen, Peter Potapov, Rebecca Moore, Science EngineeringLand UseGlobal Forest ChangeForestryHigh-resolution Global Maps	2013	11.2K
TensorFlow: A system for large-scale machine learning Martı́n Abadi, Paul Barham, Jianmin Chen, arXiv (Cornell University) Cluster ComputingEngineeringMachine LearningMachine Learning ToolComputer Architecture	2016	8.8K
A Concordance Correlation Coefficient to Evaluate Reproducibility Biometrics Reproducibility StudiesEngineeringMeasurementConcordance Correlation CoefficientAccuracy And Precision	1989	8.5K
Geostatistics for Natural Resources Evaluation Timothy C. Coburn, Pierre Goovaerts Technometrics Land UseSpatial UncertaintyGeocomputationSpatial ModelingEarth Science	2000	4.1K
Climatologies at high resolution for the earth’s land surface areas Dirk Nikolaus Karger, Olaf Conrad, Jürgen Böhner, Zurich Open Repository and Archive (University of Zurich) Earth ObservationHigh ResolutionEngineeringGeomorphologyLand Use	2017	3.8K
Climatologies at high resolution for the earth’s land surface areas Scientific Data	2017	3.7K
On digital soil mapping Alex B. McBratney, Maria de Lourdes Mendonça-Santos, Budiman Minasny Geoderma Soil PedologyCartographyPrecision AgricultureEngineeringSoil Classification	2003	3.5K

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