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1 |
Model-based analysis of the image generation quality of adversarial latent autoencoders for industrial machine vision
Yermakov, Ruslan. - Aachen : Universitätsbibliothek der RWTH Aachen, 2023
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2 |
Generating a New Reality
Berkeley, CA : Apress, 2021, 1st edition
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3 |
A pore space reconstruction method of shale based on autoencoders and generative adversarial networks
Enthalten in Computational geosciences 4.8.2021: 1-17
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4 |
Adversarial dual autoencoders for trust-aware recommendation
Enthalten in Neural computing & applications 27.1.2021: 1-11
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5 |
A fusion of deep convolutional generative adversarial networks and sequence to sequence autoencoders for acoustic scene classification
Amiriparian, Shahin. - Augsburg : Universität Augsburg, 2018
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6 |
Towards cross-lingual distributed representations without parallel text trained with adversarial autoencoders
Miceli Barone, Antonio Valerio. - Aachen : Universitätsbibliothek der RWTH Aachen, 2016
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7 |
Adversarial and variational autoencoders improve metagenomic binning
Enthalten in Communications biology Bd. 6, 21.10.2023, Nr. 1, date:12.2023: 1-10
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8 |
Anomaly detection by using a combination of generative adversarial networks and convolutional autoencoders
Enthalten in European Association for Speech, Signal and Image Processing: EURASIP journal on advances in signal processing Bd. 2022, 22.11.2022, Nr. 1, date:12.2022: 1-13
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9 |
CH-Net: Deep adversarial autoencoders for semantic segmentation in X-ray images of cabin baggage screening at airports
Enthalten in Journal of transportation security Bd. 13, 6.7.2020, Nr. 1-2, date:6.2020: 71-89
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10 |
Convolutional Variational Autoencoders and Resampling Techniques with Generative Adversarial Network for Enhancing Internet of Thing Security
Enthalten in Pattern recognition and image analysis Bd. 34, 17.10.2024, Nr. 3, date:9.2024: 562-569
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