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Service hours in Frankfurt am Main from 1 December 2025: Monday to Friday 9:00-18:00 and Saturday 10:00-16:00
Ergebnis der Suche nach:
"Machine Learning"
im Bestand: Gesamter Bestand
33201 - 33210 von 33501
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33201
Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra
Enthalten in BMC bioinformatics Bd. 24, 9.1.2023, Nr. 1, date:12.2023: 1-15
33202
Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity
Enthalten in BMC cardiovascular disorders Bd. 25, 27.10.2025, Nr. 1, date:12.2025: 1-13
33203
Using unsupervised machine learning to classify behavioral risk markers of bacterial vaginosis
Enthalten in Archives of gynecology and obstetrics Bd. 309, 3.2.2024, Nr. 3, date:3.2024: 1053-1063
33204
Using visible and NIR hyperspectral imaging and machine learning for nondestructive detection of nutrient contents in sorghum
Enthalten in Scientific reports Bd. 15, 19.2.2025, Nr. 1, date:12.2025: 1-14
33205
Using weak signals to predict spontaneous breathing trial success: a machine learning approach
Enthalten in Intensive Care Medicine Experimental Bd. 13, 18.3.2025, Nr. 1, date:12.2025: 1-14
33206
Using wearable sensors and machine learning to assess upper limb function in Huntington’s disease
Enthalten in Communications medicine Bd. 5, 25.2.2025, Nr. 1, date:12.2025: 1-9
33207
Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator
Enthalten in Scientific reports Bd. 15, 9.1.2025, Nr. 1, date:12.2025: 1-11
33208
Utilising energy function and variational inference training for learning a graph neural network architecture
Enthalten in Machine learning Bd. 113, 23.1.2024, Nr. 3, date:3.2024: 1219-1241
33209
Utilising machine learning algorithms to predict the Marshall characteristics of asphalt pavement layers
Enthalten in Innovative infrastructure solutions Bd. 9, 14.9.2024, Nr. 10, date:10.2024: 1-22
33210
Utilising unsupervised machine learning and IoT for cost-effective anomaly detection in multi-layer wire arc additive manufacturing
Enthalten in The international journal of advanced manufacturing technology Bd. 135, 24.10.2024, Nr. 5-6, date:11.2024: 2957-2974
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