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

32391 - 32400 von 32705
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Artikel 32391 Using natural history to guide supervised machine learning for cryptic species delimitation with genetic data
Enthalten in Frontiers in zoology Bd. 19, 22.2.2022, Nr. 1, date:12.2022: 1-15
Online Ressource
Artikel 32392 Using natural language processing and machine learning to identify breast cancer local recurrence
Enthalten in BMC bioinformatics Bd. 19, 28.12.2018, Nr. 17, date:12.2018: 65-74
Online Ressource
Artikel 32393 Using of Machine Learning Capabilities to Predict Double Phosphate Structures for Biomedical Applications
Enthalten in Journal of surface investigation Bd. 18, 15.7.2024, Nr. 3, date:6.2024: 633-640
Online Ressource
Artikel 32394 USING OPEN DATA CUBE ON THE CLOUD TO INVESTIGATE FOOD SECURITY BY MEANS OF CROPLAND CHANGES IN DJIBOUTI
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLIII-B3-2022, 2022: 1039-1044. 6 S.
Online Ressource
Artikel 32395 Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms
Enthalten in Water resources management Bd. 36, 17.1.2022, Nr. 2, date:1.2022: 699-716
Online Ressource
Artikel 32396 Using Passive Multi-Modal Sensor Data for Thermal Simulation of Urban Surfaces
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-2-2024, 2024: 17-24. 8 S.
Online Ressource
Artikel 32397 Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer
Enthalten in Oncogene Bd. 44, 26.2.2025, Nr. 19, date:5.2025: 1387-1399
Online Ressource
Artikel 32398 Using published pathway figures in enrichment analysis and machine learning
Enthalten in BMC genomics Bd. 24, 25.11.2023, Nr. 1, date:12.2023: 1-13
Online Ressource
Artikel 32399 Using quantum atomics and machine learning to advance picotechnology
Enthalten in Theoretical chemistry accounts Bd. 143, 26.9.2024, Nr. 10, date:10.2024: 1-9
Online Ressource
Artikel 32400 Using remote sensing data for geological mapping in semi-arid environment: a machine learning approach
Enthalten in Earth science informatics Bd. 15, 3.2.2022, Nr. 1, date:3.2022: 485-496
Online Ressource


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