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"Machine Learning"
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16671 - 16680 von 16964
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16671
UNSUPERVISED METHODOLOGY TO IN-SEASON MAPPING OF SUMMER CROPS IN URUGUAY WITH MODIS EVI’S TEMPORAL SERIES AND MACHINE LEARNING
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-3/W12-2020, 2020: 171-176
16672
Unveiling Adolescent Suicidality: Holistic Analysis of Protective and Risk Factors Using Multiple Machine Learning Algorithms
Enthalten in Journal of youth and adolescence Bd. 53, 20.11.2023, Nr. 3, date:3.2024: 507-525
16673
Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach
Enthalten in Scientific reports Bd. 15, 26.4.2025, Nr. 1, date:12.2025: 1-18
16674
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling
Enthalten in npj computational materials Bd. 11, 6.6.2025, Nr. 1, date:12.2025: 1-13
16675
Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models
Enthalten in BMC medicine Bd. 23, 19.5.2025, Nr. 1, date:12.2025: 1-12
16676
Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors
Enthalten in The journal of headache and pain Bd. 26, 6.5.2025, Nr. 1, date:12.2025: 1-14
16677
Unveiling sustainable tourism themes with machine learning based topic modeling
Enthalten in Discover sustainability Bd. 6, 14.4.2025, Nr. 1, date:12.2025: 1-28
16678
Unveiling the antiviral inhibitory activity of ebselen and ebsulfur derivatives on SARS-CoV-2 using machine learning-based QSAR, LB-PaCS-MD, and experimental assay
Enthalten in Scientific reports Bd. 15, 26.2.2025, Nr. 1, date:12.2025: 1-12
16679
Unveiling the effect of composition on nuclear waste immobilization glasses’ durability by nonparametric machine learning
Enthalten in npj Materials degradation Bd. 8, 15.4.2024, Nr. 1, date:12.2024: 1-11
16680
Unveiling the epilepsy enigma: an agile and optimal machine learning approach for detecting inter-ictal state from electroencephalogram signals
Enthalten in International journal of information technology Bd. 16, 23.8.2024, Nr. 8, date:12.2024: 5149-5172
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