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27321 |
Spatial Clustering of Primary Geochemical Halos Using Unsupervised Machine Learning in Sari Gunay Gold Deposit, Iran
Enthalten in Mining, metallurgy & exploration Bd. 41, 16.9.2024, Nr. 5, date:10.2024: 2741-2760
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27322 |
Spatial distribution and machine learning prediction of sexually transmitted infections and associated factors among sexually active men and women in Ethiopia, evidence from EDHS 2016
Enthalten in BMC infectious diseases Bd. 23, 23.1.2023, Nr. 1, date:12.2023: 1-16
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27323 |
SPATIAL DOWNSCALING OF GPM IMERG V06 GRIDDED PRECIPITATION USING MACHINE LEARNING ALGORITHMS
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W6-2022, 2023: 327-332. 6 S.
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27324 |
Spatial dynamics of soil organic carbon and total nitrogen concerning aggregate size fractions using machine learning models
Enthalten in Soil ecology letters Bd. 7, 28.4.2025, Nr. 2, date:6.2025: 1-19
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27325 |
Spatial entropy as an inductive bias for vision transformers
Enthalten in Machine learning Bd. 113, 17.7.2024, Nr. 9, date:9.2024: 6945-6975
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27326 |
Spatial indexing and searching using parallel wavelet tree
Enthalten in International journal of information technology Bd. 15, 25.8.2023, Nr. 7, date:10.2023: 3583-3591
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27327 |
Spatial Interpolation Using Machine Learning: From Patterns and Regularities to Block Models
Enthalten in Natural resources research Bd. 33, 25.11.2023, Nr. 1, date:2.2024: 129-161
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27328 |
SPATIAL INVENTORY OF SOLAR PHOTOVOLTAIC (PV) INSTALLATIONS USING REMOTE SENSING AND MACHINE LEARNING: CASE OF PAMPANGA PROVINCE, PHILIPPINES
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W9-2024, 2024: 115-123. 9 S.
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27329 |
Spatial Mapping for Multi-Hazard Land Management in Sparsely Vegetated Watersheds Using Machine Learning Algorithms
Enthalten in Environmental earth sciences Bd. 83, 20.7.2024, Nr. 15, date:7.2024: 1-23
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27330 |
Spatial mapping of artesian zone at Iraqi southern desert using a GIS-based random forest machine learning model
Enthalten in Modeling earth systems and environment Bd. 2, 14.6.2016, Nr. 2, date:6.2016: 1-17
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