Found: 7
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Using machine learning to improve predictions and provide insight into fluvial sediment transport.
- Published in:
- Hydrological Processes, 2022, v. 36, n. 8, p. 1, doi. 10.1002/hyp.14648
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- Article
SPATIAL FACTOR MODELS FOR HIGH-DIMENSIONAL AND LARGE SPATIAL DATA: AN APPLICATION IN FOREST VARIABLE MAPPING.
- Published in:
- Statistica Sinica, 2019, v. 29, n. 3, p. 1155, doi. 10.5705/ss.202018.0005
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- Article
Quantifying and correcting geolocation error in spaceborne LiDAR forest canopy observations using high spatial accuracy data: A Bayesian model approach.
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- Environmetrics, 2024, v. 35, n. 4, p. 1, doi. 10.1002/env.2840
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- Article
Are beta-2-agonists or anticholinergics more effective for treating COPD?
- Published in:
- Journal of Family Practice, 2004, v. 53, n. 6, p. 494
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- Article
Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data.
- Published in:
- Remote Sensing, 2021, v. 13, n. 10, p. 1863, doi. 10.3390/rs13101863
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- Article
Harnessing the Temporal Dimension to Improve Object-Based Image Analysis Classification of Wetlands.
- Published in:
- Remote Sensing, 2018, v. 10, n. 9, p. 1467, doi. 10.3390/rs10091467
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- Article
Dynamic spatial regression models for space-varying forest stand tables.
- Published in:
- Environmetrics, 2014, v. 25, n. 8, p. 596, doi. 10.1002/env.2322
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- Article