Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 101 for “"GANs"”.
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Refining inferred road maps using GANs
Mapping road networks is both expensive and labor-intensive. A variety of automated mapping approaches have been proposed in recent years, but these schemes often produce maps that are messy, error-prone, or visually unappealing. To fix this, we train a conditional Wasserstein GAN to refine the …
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Co-generation with GANs using AIS based HMC
… particularly generative adversarial nets (GANs). Therefore, in this paper, we study the occurring challenges for co-generation with GANs. To address those challenges we develop an annealed importance sampling based Hamiltonian Monte Carlo co-generation algorithm. The presented approach …
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Learning non-stationary SVBRDFs using GANs and differentiable rendering
… in complex neural network models such as GANs, opening up opportunities for more applications of deep learning methods in the computer graphics pipeline.
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Deep Learning Image Augmentation using Inpainting with Partial Convolution and GANs
The 21st century has seen the remarkable transformation of machine vision by deep learning. This has enabled intelligent systems like autonomous vehicles and facial recognition software. However, the success of deep learning is largely predicated on the availability of sufficient data; in many …
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Generative adversarial networks for fine art generation
Generative Adversarial Networks (GANs), a generative modelling technique most commonly used for image generation, have recently been applied to the task of fine art generation. Wasserstein GANs and GANHack techniques have not been applied in GANs that generate fine art, despite their showing …
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Machine Learning-Aided Aerospace Applications with Generative Adversarial Networks
… technologies. Generative Adversarial Networks (GANs), a subset of generative models, have shown remarkable proficiency at this task, surpassing other state-of-the-art approaches. They have become an extraordinary tool for addressing critical challenges like data scarcity in complex environmental …
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An Application of Generative Adversarial Networks to One-Dimensional Value-at-Risk
… neural networks. This minor dissertation applies GANs to recover target statistical distributions. GANs have a distinctive training architecture designed to create examples that reproduce target data samples. These models have been applied successfully in high-dimensional domains such as natural …
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Machine Learning for 3D Visualisation Using Generative Models
… introduction of generative adversarial networks (GANs), which had achieved great success in their ability to generate images comparable to real photos with minimum human intervention. These networks can generalise to a multitude of desired outputs, especially in image-to-image problems and image …
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Machine Learning for 3D Visualisation Using Generative Models
… introduction of generative adversarial networks (GANs), which had achieved great success in their ability to generate images comparable to real photos with minimum human intervention. These networks can generalise to a multitude of desired outputs, especially in image-to-image problems and image …
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Using generative modelling in healthcare
… (VAEs) and Generative Adversarial Networks (GANs) and their variants. Subsequently, we shall review some new developed imputation methods which are based on GANs and VAEs. We shall assess their performance under various missingness scenarios via accordingly designed experiments and simulation …
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G A N mask R-CNN : instance semantic segmentation benefits from generative adversarial networks
… we can lay the problem of predicting masks as a GANs game framework: We can think the ground truth mask is drawn from the true distribution, and a ConvNet like Mask R-CNN is an implicit model that infers the true distribution. In GANs terms, Mask R-CNN is the generator who reconstructs a mask as …
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Natural video synthesis with Generative Adversarial Networks
Generative Adversarial Networks (GANs) are the state of the art neural network models for image generation, but the use of GANs for video generation is still largely unexplored. This thesis introduces new GAN based video generation methods by proposing the technique of model inflation and the …
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Generative methods for image synthesis with applications to medical imaging
… hybrid model of generative adversarial networks (GANs) and transformer networks for image synthesis. We propose a method that combines GANs with transformer networks to address the translation and super-resolution of medical images. We also present a model for inpainting of images. Finally, we …
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Belief propagation generative adversarial networks
Generative adversarial networks (GANs) are a class of generative models based on a minimax game. They have led to significant improvement in the field of unsupervised learning, especially image generation. However, most works in GANs are based on learning the distribution of the input dataset …
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PacGAN: The power of two samples in generative adversarial networks
Generative adversarial networks (GANs) are innovative techniques for learning generative models of complex data distributions from samples. Despite remarkable recent improvements in generating realistic images, one of their major shortcomings is the fact that in practice, they tend to produce …
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Generative modelling and adversarial learning
… produce more realistic samples. Unlike existing GANs, which alternately train a generator and a discriminator using a pre-defined adversarial objective function, different adversarial training objectives are utilised as mutation operations and train a population of generators to adapt to the …
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Feeding habits of sardine (Sardinops sagax) in relation to their spawning activities
… sardine (Sardinops sagax) from St Helena Bay and Gans Bay in the Southern Benguela was studied between February and April 2011 and related to reproduction. Feeding intensity of 373 sardine was calculated and correlated with caudal length across different gonad maturity and fat stages. Feeding …
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Feeding habits of sardine (Sardinops sagax) in relation to their spawning activities
… sardine (Sardinops sagax) from St Helena Bay and Gans Bay in the Southern Benguela was studied between February and April 2011 and related to reproduction. Feeding intensity of 373 sardine was calculated and correlated with caudal length across different gonad maturity and fat stages. Feeding …
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Development and Evaluation of Generative Adversarial Networks for Predicting Central Hemodynamics
… the use of generative adversarial networks (GANs) in combination with cardiovascular mechanistic models to estimate central hemodynamic values from ECG and tabular data. Three hemodynamic quantities form the focus of this work: mean pulmonary artery pressure (mPAP), mean pulmonary capillary …
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A Minimax Approach for Learning Gaussian Mixtures
Generative adversarial networks (GANs) learn the distribution of observed samples through a zero-sum game between two machine players, a generator and a discriminator. While GANs achieve great success in learning the complex distribution of image, sound, and text data, they perform suboptimally in …
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