Results 61 to 70 of about 221,929 (334)
Wasserstein Introspective Neural Networks
, 2018 We present Wasserstein introspective neural networks (WINN) that are both a generator and a discriminator within a single model. WINN provides a significant improvement over the recent introspective neural networks (INN) method by enhancing INN's ...
Fan, Fan +3 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
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Bidirectional Conditional Generative Adversarial Networks
, 2018 Conditional Generative Adversarial Networks (cGANs) are generative models that can produce data samples ($x$) conditioned on both latent variables ($z$) and known auxiliary information ($c$). We propose the Bidirectional cGAN (BiCoGAN), which effectively
AbdAlmageed, Wael +3 more
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Spatial evolutionary generative adversarial networks [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference, 2019 Generative adversary networks (GANs) suffer from training pathologies such as instability and mode collapse. These pathologies mainly arise from a lack of diversity in their adversarial interactions. Evolutionary generative adversarial networks apply the principles of evolutionary computation to mitigate these problems.
Toutouh, Jamal +2 more
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A generative adversarial network to Reinhard stain normalization for histopathology image analysis
Ain Shams Engineering JournalHistopathology image analysis is paramount importance for accurate diagnosing diseases and gaining insight into tissue properties. The significant challenge of staining variability continues.
Afnan M. Alhassan
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Attribute-Aware Generative Design With Generative Adversarial Networks
IEEE Access, 2020 The designers' tendency to adhere to a specific mental set and heavy emotional investment in their initial ideas often limit their ability to innovate during the design ideation process.
Chenxi Yuan, Mohsen Moghaddam
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Компьютерная оптикаSingle-pixel imaging is a promising image acquisition method that provides an alternative to traditional imaging methods using multi-pixel matrices. However, algorithmic image reconstruction from measurements of a single-pixel camera is a non-trivial ...
D.V. Babukhin, A.A. Reutov, D.V. Sych
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Review of Application of Generative Adversarial Networks in Image Restoration [PDF]
Jisuanji kexue yu tansuoWith the rapid development of generative adversarial networks, many image restoration problems that are difficult to solve based on traditional methods have gained new research approaches.
GONG Ying, XU Wentao, ZHAO Ce, WANG Binjun
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Adversarial Variational Optimization of Non-Differentiable Simulators [PDF]
, 2019 Complex computer simulators are increasingly used across fields of science as generative models tying parameters of an underlying theory to experimental observations.
Cranmer, Kyle +2 more
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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.
Yang, Xiaogang +8 more
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