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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 |
Structural health monitoring of arch dams with deep learning: a comparative study of recurrent neural networks in daily, bi-monthly, and monthly predictions
Enthalten in Journal of civil structural health monitoring 13.4.2025: 1-16
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3 |
Missing Object Detection and Tracking from Video Surveillance Camera Footage Based on Deep Learning Through Convolutional Gated Recurrent Neural Networks (CGRNN)
Enthalten in Journal of electrical engineering & technology 8.4.2025: 1-9
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4 |
Human activity recognition using a bagging-based deep learning framework with convolutional capsule networks and spiking neural networks
Enthalten in International journal of information technology 26.2.2025: 1-19
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5 |
[Künstliche Intelligenz und Hirnforschung]
Artificial intelligence and brain research
Krauss, Patrick. - Berlin, Germany : Springer, [2024]
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6 |
[Künstliche Intelligenz und Hirnforschung]
Artificial Intelligence and Brain Research
Krauss, Patrick. - Berlin, Heidelberg : Springer Berlin Heidelberg, Imprint: Springer, 2024, 1st ed. 2024
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7 |
Physical Artificial Neural Networks - Optical and Atomic Approaches to Deep Learning
Hansmann, Kai Niklas. - Darmstadt : Universitäts- und Landesbibliothek, 2024
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8 |
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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9 |
Ensemble learning based lung and colon cancer classification with pre-trained deep neural networks
Enthalten in Health and Technology 6.11.2024: 1-13
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10 |
Advancing brain tumor classification accuracy through deep learning: harnessing radimagenet pre-trained convolutional neural networks, ensemble learning, and machine learning classifiers on MRI brain images
Enthalten in Multimedia tools and applications 11.3.2024: 1-29
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