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Ergebnis der Suche nach: tit all "Support Vector Machines"
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Artikel 51 Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
Enthalten in BMC bioinformatics Bd. 6, 22.6.2005, Nr. 1, date:12.2005: 1-12
Online Ressource
Artikel 52 Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries
Enthalten in Chemistry central journal Bd. 6, 23.11.2012, Nr. 1, date:12.2012: 1-14
Online Ressource
Artikel 53 Enhancement of hepatitis virus immunoassay outcome predictions in imbalanced routine pathology data by data balancing and feature selection before the application of support vector machines
Enthalten in BMC medical informatics and decision making Bd. 17, 14.8.2017, Nr. 1, date:12.2017: 1-11
Online Ressource
Artikel 54 Ensemble and optimization algorithm in support vector machines for classification of wheat genotypes
Enthalten in Scientific reports Bd. 14, 30.9.2024, Nr. 1, date:12.2024: 1-19
Online Ressource
Artikel 55 eRFSVM: a hybrid classifier to predict enhancers-integrating random forests with support vector machines
Enthalten in Hereditas Bd. 153, 30.6.2016, Nr. 1, date:12.2016: 1-11
Online Ressource
Artikel 56 Estimating biophysical parameters of rice with remote sensing data using support vector machines
Enthalten in Science China / Life sciences Bd. 54, 16.3.2011, Nr. 3, date:3.2011: 272-281
Online Ressource
Artikel 57 Facial expression recognition using three-stage support vector machines
Enthalten in Visual computing for industry, biomedicine, and art Bd. 2, 16.12.2019, Nr. 1, date:12.2019: 1-9
Online Ressource
Artikel 58 Fluorescence Guided Raman Spectroscopy enables the training of robust support vector machines for the detection of tumour marker proteins
Enthalten in Scientific reports Bd. 15, 3.7.2025, Nr. 1, date:12.2025: 1-14
Online Ressource
Artikel 59 Harnessing the evolutionary information on oxygen binding proteins through Support Vector Machines based modules
Enthalten in Biomed Central (London): BMC Research Notes Bd. 11, 11.5.2018, Nr. 1, date:12.2018: 1-8
Online Ressource
Artikel 60 Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems
Enthalten in Plant methods Bd. 14, 3.10.2018, Nr. 1, date:12.2018: 1-13
Online Ressource


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