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Ergebnis der Suche nach: "Machine Learning"
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26661 - 26670 von 29045
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Artikel 26661 Rational design and glass-forming ability prediction of bulk metallic glasses via interpretable machine learning
Enthalten in Journal of materials science Bd. 58, 19.5.2023, Nr. 21, date:6.2023: 8833-8844
Online Ressource
Artikel 26662 RCC-Supporter: supporting renal cell carcinoma treatment decision-making using machine learning
Enthalten in BMC medical informatics and decision making Bd. 24, 16.9.2024, Nr. 2, date:4.2024: 1-15
Online Ressource
Artikel 26663 Re-assessing accuracy degradation: a framework for understanding DNN behavior on similar-but-non-identical test datasets
Enthalten in Machine learning Bd. 114, 14.2.2025, Nr. 3, date:3.2025: 1-22
Online Ressource
Artikel 26664 Re-evaluation of machine learning models for predicting ultimate bearing capacity of piles through SHAP and Joint Shapley methods
Enthalten in Neural computing & applications Bd. 36, 16.10.2023, Nr. 2, date:1.2024: 697-715
Online Ressource
Artikel 26665 Re-evaluation of publicly available gene-expression databases using machine-learning yields a maximum prognostic power in breast cancer
Enthalten in Scientific reports Bd. 13, 5.10.2023, Nr. 1, date:12.2023: 1-14
Online Ressource
Artikel 26666 Re-investigation of functional gastrointestinal disorders utilizing a machine learning approach
Enthalten in BMC medical informatics and decision making Bd. 23, 26.8.2023, Nr. 1, date:12.2023: 1-12
Online Ressource
Artikel 26667 Reaching a desirable metastructure for passive vibration attenuation by using a machine learning approach
Enthalten in Nonlinear dynamics Bd. 112, 26.8.2024, Nr. 23, date:12.2024: 20661-20676
Online Ressource
Artikel 26668 Reaching machine learning leverage to advance performance of electrocatalytic CO2 conversion in non-aqueous deep eutectic electrolytes
Enthalten in Scientific reports Bd. 14, 21.10.2024, Nr. 1, date:12.2024: 1-18
Online Ressource
Artikel 26669 Reaching the Full Potential of Machine Learning in Mitigating Environmental Impacts of Functional Materials
Enthalten in Reviews of environmental contamination and toxicology Bd. 260, 14.12.2022, Nr. 1, date:12.2022: 1-19
Online Ressource
Artikel 26670 Reading Between the Lines: Machine Learning Ensemble and Deep Learning for Implied Threat Detection in Textual Data
Enthalten in International journal of computational intelligence systems Bd. 17, 15.7.2024, Nr. 1, date:12.2024: 1-17
Online Ressource


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