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Ergebnis der Suche nach: tit all "Support Vector Machines"
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501 - 510 von 600
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Artikel 501 On-line Time Domain Vibration and Current Signals Based Multi-fault Diagnosis of Centrifugal Pumps Using Support Vector Machines
Enthalten in Journal of nondestructive evaluation Bd. 38, 22.11.2018, Nr. 1, date:3.2019: 1-18
Online Ressource
Artikel 502 On neural quantum support vector machines
Enthalten in Quantum machine intelligence Bd. 6, 22.1.2024, Nr. 1, date:6.2024: 1-8
Online Ressource
Artikel 503 One-class support vector machines for detecting population drift in deployed machine learning medical diagnostics
Enthalten in Scientific reports Bd. 15, 9.4.2025, Nr. 1, date:12.2025: 1-8
Online Ressource
Artikel 504 Optimal classification for the diagnosis of duchenne muscular dystrophy images using support vector machines
Enthalten in International journal of computer assisted radiology and surgery Bd. 11, 17.10.2015, Nr. 9, date:9.2016: 1755-1763
Online Ressource
Artikel 505 Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines
Enthalten in Discover artificial intelligence Bd. 4, 30.10.2024, Nr. 1, date:12.2024: 1-16
Online Ressource
Artikel 506 Optimizing support vector machines for enhanced permeability prediction in sandstone reservoirs using systematic and heuristic hyperparameter tuning
Enthalten in Earth science informatics Bd. 18, 21.12.2024, Nr. 1, date:1.2025: 1-19
Online Ressource
Artikel 507 Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines
Enthalten in BMC bioinformatics Bd. 10, 22.8.2009, Nr. 1, date:12.2009: 1-15
Online Ressource
Artikel 508 Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Enthalten in BMC bioinformatics Bd. 7, 12.12.2006, Nr. 4, date:12.2006: 1-10
Online Ressource
Artikel 509 POPISK: T-cell reactivity prediction using support vector machines and string kernels
Enthalten in BMC bioinformatics Bd. 12, 15.11.2011, Nr. 1, date:12.2011: 1-11
Online Ressource
Artikel 510 Predicting beta-turns in proteins using support vector machines with fractional polynomials
Enthalten in Proteome science Bd. 11, 7.11.2013, Nr. 1, date:12.2013: 1-10
Online Ressource


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