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Servicezeiten in Frankfurt am Main ab 1. Dezember 2025: Montag bis Freitag 9–18 Uhr und Samstag 10–16 Uhr
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
32591 - 32600 von 33464
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32591
Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction
Enthalten in BMC palliative care Bd. 23, 20.5.2024, Nr. 1, date:12.2024: 1-10
32592
Towards provably efficient quantum algorithms for large-scale machine-learning models
Enthalten in Nature Communications Bd. 15, 10.1.2024, Nr. 1, date:12.2024: 1-6
32593
Towards quantifying psychiatric diagnosis using machine learning algorithms and big fMRI data
Enthalten in Big data analytics Bd. 3, 31.5.2018, Nr. 1, date:12.2018: 1-3
32594
Towards real-time secured IP camera via state machine architecture
Enthalten in International journal of information technology Bd. 16, 9.11.2023, Nr. 1, date:1.2024: 329-336
32595
Towards Regulatory-Compliant MLOps: Oravizio’s Journey from a Machine Learning Experiment to a Deployed Certified Medical Product
Enthalten in SN Computer Science Bd. 2, 19.6.2021, Nr. 5, date:9.2021: 1-14
32596
Towards Replication in Computational Cognitive Modeling: a Machine Learning Perspective
Enthalten in Computational brain & behavior Bd. 2, 14.8.2019, Nr. 3-4, date:12.2019: 242-246
32597
Towards representation learning of radar altimeter waveforms for sea ice surface classification
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-G-2025, 2025: 333-340. 8 S.
32598
Towards smart glasses for facial expression recognition using OMG and machine learning
Enthalten in Scientific reports Bd. 13, 25.9.2023, Nr. 1, date:12.2023: 1-16
32599
Towards smart scanning probe lithography: a framework accelerating nano-fabrication process with in-situ characterization via machine learning
Enthalten in Microsystems & nanoengineering Bd. 9, 10.10.2023, Nr. 1, date:12.2023: 1-14
32600
Towards sustainable construction: estimating compressive strength of waste foundry sand-blended green concrete using a hybrid machine learning approach
Enthalten in Discover civil engineering Bd. 2, 3.3.2025, Nr. 1, date:12.2025: 1-25
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