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Neuigkeiten Donnerstag, 11. September 2025: Die Deutsche Nationalbibliothek öffnet wegen eines Beschäftigtentreffens an beiden Standorten erst um 15 Uhr. // Thursday, 11 September 2025: The German National Library will not open until 15:00 due to a staff meeting at both locations.
 
 
 


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

1521 - 1530 von 29262
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Artikel 1521 General structure-activity relationship models for the inhibitors of Adenosine receptors: A machine learning approach
Enthalten in Molecular diversity 20.1.2025: 1-20
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Artikel 1522 Predicting doxorubicin-induced cardiotoxicity in breast cancer: leveraging machine learning with synthetic data
Enthalten in Medical & biological engineering & computing 20.1.2025: 1-16
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Artikel 1523 Unsupervised Object Detection using Patch Based Image Classifier and Gradient Importance Map
Enthalten in International journal of information technology 20.1.2025: 1-10
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Artikel 1524 Emotion recognition using VMD domain bandwidth and spectral features
Enthalten in International journal of information technology 19.1.2025: 1-9
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Artikel 1525 In-situ evaluation of hole quality and cutting tool condition in robotic drilling of composite materials using machine learning
Enthalten in Journal of intelligent manufacturing 19.1.2025: 1-22
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Artikel 1526 Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Enthalten in Advanced engineering materials 18.01.2025. 17 S.
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Artikel 1527 Correction: An Approach Towards Machine Learning Assisted HEMT Based Quantum Dot Sensor for Glucose Detection
Enthalten in National Academy of Sciences, India: National Academy science letters 18.1.2025: 1
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Artikel 1528 Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder
Enthalten in Neuroradiology 18.1.2025: 1-10
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Artikel 1529 Machine learning models for neurocognitive outcome prediction in preterm born infants
Enthalten in Pediatric research 18.1.2025: 1-8
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Artikel 1530 Parkinson’s disease diagnosis using deep learning model by analyzing the channels of electroencephalography signals from substansia niagra and ventral tegmental area regions of human brain
Enthalten in International journal of information technology 18.1.2025: 1-24
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