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1 |
Deep learning-based prediction of particle size distributions in construction and demolition waste recycling using convolutional neural networks on 3D laser triangulation data
Kroell, Nils. - Aachen : Universitätsbibliothek der RWTH Aachen, 2025
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2 |
Deep learning in-depth analysis of crystal graph convolutional neural networks: A new era in materials discovery and its applications
Enthalten in Nanotechnology reviews Bd. 14, 2025, Nr. 1. 24 S.
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3 |
Physical Artificial Neural Networks - Optical and Atomic Approaches to Deep Learning
Hansmann, Kai Niklas. - Darmstadt : Universitäts- und Landesbibliothek, 2024
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4 |
Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event prediction with deep learning
Heinrich, Kai. - Würzburg : Universität Würzburg, 2024
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5 |
A wholistic view of continual learning with deep neural networks: forgotten lessons and the bridge to active and open world learning
Mundt, Martin. - Frankfurt am Main : Universitätsbibliothek Johann Christian Senckenberg, 2023
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6 |
Geometric deep learning and equivariant neural networks
Enthalten in Artificial intelligence review 4.6.2023: 1-58
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7 |
Deep neural networks and machine learning radiomics modelling for prediction of relapse in mantle cell lymphoma
Lisson, Catharina Silvia. - Ulm : Universität Ulm, 2022
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8 |
Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research
Bodesheim, Paul. - Jena : Friedrich-Schiller-Universität Jena, 2022
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9 |
Reduction of Platelet Outdating and Shortage by Forecasting Demand With Statistical Learning and Deep Neural Networks: Modeling Study
Schilling, Maximilian. - Aachen : Universitätsbibliothek der RWTH Aachen, 2022
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10 |
Detecting and responding to hostile disinformation activities on social media using machine learning and deep neural networks
Enthalten in Neural computing & applications 9.6.2022: 1-23
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