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Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

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Artikel 26871 Machine learning techniques in monitoring and controlling friction stir welding process: a critical review
Enthalten in Discover applied sciences Bd. 7, 31.5.2025, Nr. 6, date:6.2025: 1-44
Online Ressource
Artikel 26872 Machine learning techniques on homological persistence features for prostate cancer diagnosis
Enthalten in BMC bioinformatics Bd. 23, 12.11.2022, Nr. 1, date:12.2022: 1-22
Online Ressource
Artikel 26873 Machine learning techniques on spatio-temporal data for landslide susceptibility assessment at Dieng Mountainous Region, Banjarnegara district, Central Java, Indonesia
Enthalten in Natural hazards Bd. 121, 11.3.2025, Nr. 8, date:5.2025: 9925-9962
Online Ressource
Artikel 26874 Machine Learning Techniques Outperform Conventional Statistical Methods in the Prediction of High Risk QTc Prolongation Related to a Drug-Drug Interaction
Enthalten in Journal of medical systems Bd. 46, 23.11.2022, Nr. 12, date:12.2022: 1-10
Online Ressource
Artikel 26875 Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement
Enthalten in Materials and structures Bd. 55, 16.4.2022, Nr. 4, date:5.2022: 1-16
Online Ressource
Artikel 26876 Machine Learning Techniques to Identify Dementia
Enthalten in SN Computer Science Bd. 1, 10.4.2020, Nr. 3, date:5.2020: 1-6
Online Ressource
Artikel 26877 Machine Learning Techniques to Identify Dementia
Enthalten in SN Computer Science Bd. 1, 10.4.2020, Nr. 3, date:5.2020: 1-6
Online Ressource
Artikel 26878 Machine learning techniques to identify putative genes involved in nitrogen catabolite repression in the yeast Saccharomyces cerevisiae
Enthalten in Biomed Central (London): BMC proceedings Bd. 2, 17.12.2008, Nr. 4, date:12.2008: 1-8
Online Ressource
Artikel 26879 Machine learning techniques to predict daily rainfall amount
Enthalten in Journal of Big Data Bd. 8, 7.12.2021, Nr. 1, date:12.2021: 1-11
Online Ressource
Artikel 26880 Machine Learning Techniques to Predict Rock Strength Parameters
Enthalten in Rock mechanics and rock engineering Bd. 55, 6.1.2022, Nr. 3, date:3.2022: 1721-1741
Online Ressource


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