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

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Artikel 26781 Machine learning techniques implementation for detection of grape leaf disease
Enthalten in Multimedia tools and applications Bd. 82, 28.2.2023, Nr. 20, date:8.2023: 30709-30731
Online Ressource
Artikel 26782 Machine learning techniques in disease forecasting: a case study on rice blast prediction
Enthalten in BMC bioinformatics Bd. 7, 03.11.2006, Nr. 1, date:12.2006: 1-16
Online Ressource
Artikel 26783 Machine learning techniques in eating behavior e-coaching
Enthalten in Personal and ubiquitous computing Bd. 21, 8.6.2017, Nr. 4, date:8.2017: 645-659
Online Ressource
Artikel 26784 Machine learning techniques in estimation of eggplant crop evapotranspiration
Enthalten in Applied water science Bd. 13, 22.5.2023, Nr. 6, date:6.2023: 1-30
Online Ressource
Artikel 26785 Machine learning techniques in hepatic encephalopathy: a scoping review
Enthalten in BMC medical informatics and decision making Bd. 25, 1.9.2025, Nr. 1, date:12.2025: 1-16
Online Ressource
Artikel 26786 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 26787 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 26788 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 26789 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 26790 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


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