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Tomographic reconstruction with a generative adversarial network [PDF]
Journal of Synchrotron Radiation, 2020 This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm uses a generative adversarial network (GAN) to solve the inverse of the Radon transform directly. It works for independent sinograms without additional training steps.
Maik Kahnt +9 more
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Generative Adversarial Networks in finance: an overview [PDF]
SSRN Electronic Journal, 2021 Modelling in finance is a challenging task: the data often has complex statistical properties and its inner workings are largely unknown. Deep learning algorithms are making progress in the field of data-driven modelling, but the lack of sufficient data to train these models is currently holding back several new applications.
Joerg Osterrieder, Florian Eckerli
openaire +4 more sources
PHom-GeM: Persistent Homology for Generative Models [PDF]
, 2019 Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial data.
Charlier, Jeremy +2 more
core +2 more sources
Generative Adversarial Networks in Retinal Image Classification
Applied Sciences, 2023 The recent introduction of generative adversarial networks has demonstrated remarkable capabilities in generating images that are nearly indistinguishable from real ones.
Francesco Mercaldo +4 more
doaj +1 more source
The Bures Metric for Generative Adversarial Networks [PDF]
, 2021 Additional empirical ...
de Meulemeester, Hannes +4 more
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Quantum generative adversarial networks [PDF]
Physical Review A, 2018 10 pages, 8 ...
Nathan Killoran +1 more
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An Adaptive Generative Adversarial Network for Cardiac Segmentation from X-ray Chest Radiographs
Applied Sciences, 2020 Medical image segmentation is a classic challenging problem. The segmentation of parts of interest in cardiac medical images is a basic task for cardiac image diagnosis and guided surgery.
Xiaochang Wu, Xiaolin Tian
doaj +1 more source
Application of deep learning in recognition of accrued earnings management
Heliyon, 2023 We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by ...
Jia Li, Zhoutianyang Sun
doaj +1 more source
Adversarial Gaussian Denoiser for Multiple-Level Image Denoising
Sensors, 2021 Image denoising is a challenging task that is essential in numerous computer vision and image processing problems. This study proposes and applies a generative adversarial network-based image denoising training architecture to multiple-level Gaussian ...
Aamir Khan +4 more
doaj +1 more source
Evolutionary Generative Adversarial Networks [PDF]
IEEE Transactions on Evolutionary Computation, 2018 14 pages, 8 ...
Chaoyue Wang +3 more
openalex +5 more sources