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34351 - 34360 von 34669
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Artikel 34351 Using Machine Learning techniques in phenomenological studies on flavour physics
Enthalten in Journal of high energy physics Bd. 2022, 19.7.2022, Nr. 7, date:7.2022: 1-43
Online Ressource
Artikel 34352 Using Machine Learning Techniques to Detect Defects in Images of Metal Structures
Enthalten in Pattern recognition and image analysis Bd. 31, 21.9.2021, Nr. 3, date:7.2021: 506-512
Online Ressource
Artikel 34353 Using Machine Learning Techniques to Detect Parallel Patterns of Multi-threaded Applications
Enthalten in International journal of parallel programming Bd. 44, 4.11.2015, Nr. 4, date:8.2016: 867-900
Online Ressource
Artikel 34354 USING MACHINE LEARNING TECHNIQUES TO FILTER VEGETATION IN COLORIZED SFM POINT CLOUDS OF SOIL SURFACES
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-1/W2-2023, 2023: 163-170. 8 S.
Online Ressource
Artikel 34355 Using machine learning techniques to predict antimicrobial resistance in stone disease patients
Enthalten in World journal of urology Bd. 40, 26.5.2022, Nr. 7, date:7.2022: 1731-1736
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Artikel 34356 Using machine learning techniques to predict the cost of repairing hard failures in underground fiber optics networks
Enthalten in Journal of Big Data Bd. 7, 24.8.2020, Nr. 1, date:12.2020: 1-16
Online Ressource
Artikel 34357 Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data
Enthalten in Scientific reports Bd. 14, 4.3.2024, Nr. 1, date:12.2024: 1-11
Online Ressource
Artikel 34358 Using Machine Learning Techniques to Test the Load Capacity Curve Hypothesis: A Classifier-Lasso Application on Global Panel Data
Enthalten in Biophysical economics and sustainability Bd. 10, 19.2.2025, Nr. 1, date:6.2025: 1-18
Online Ressource
Artikel 34359 Using machine learning to assist with the selection of security controls during security assessment
Enthalten in Empirical software engineering Bd. 25, 13.4.2020, Nr. 4, date:7.2020: 2550-2582
Online Ressource
Artikel 34360 Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials
Enthalten in Theoretical and applied genetics Bd. 137, 23.7.2024, Nr. 8, date:8.2024: 1-13
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