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1661 |
Design Principles for Falsifiable, Replicable and Reproducible Empirical Machine Learning Research
Vranješ, Daniel. - Wadern : Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2024
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1662 |
Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning
Schmidt-Barbo, Paul. - Augsburg : Universität Augsburg, 2024
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1663 |
Determination of droplet size from wide-angle light scattering image data using convolutional neural networks
Kirsten, Tom. - Ulm : Universität Ulm, 2024
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1664 |
Development of a machine learning-based surrogate model for friction prediction in textured journal bearings
Wang, Yujun. - Aachen : Universitätsbibliothek der RWTH Aachen, 2024
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1665 |
Doctor’s Orders—Why Radiologists Should Consider Adjusting Commercial Machine Learning Applications in Chest Radiography to Fit Their Specific Needs
Schweikhard, Frank P.. - Greifswald : Universität Greifswald, 2024
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1666 |
Drivers of heterogeneity in tundra vegetation productivity on the Yamal Peninsula, Siberia, Russia
Tassone, Morgan S.. - IOP Publishing, 2024
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1667 |
Einsatz von Künstlicher Intelligenz bei der wissenschaftlichen Literaturrecherche: ein Überblick
Da Silva Cardoso, Heike. - Augsburg : Universität Augsburg, 2024
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1668 |
Einsatz von Machine Learning zur Erstellung von XPlanGML
Zilz, Julian. - Berlin : KartDok - Repositorium Kartographie Staatsbibliothek zu Berlin - Preußischer Kulturbesitz - Kartenabteilung -, 2024
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1669 |
Electroretinogram Analysis Using a Short-Time Fourier Transform and Machine Learning Techniques
Albasu, Faisal. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2024
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1670 |
Enhancing 3D reconstruction accuracy of FIB tomography data using multi-voltage images and multimodal machine learning
Sardhara, Trushal. - Hamburg : Technische Universität Hamburg. Universitätsbibliothek, 2024
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