Results 51 to 60 of about 124,232 (320)
Dairy Goat Image Generation Based on Improved-Self-Attention Generative Adversarial Networks
IEEE Access, 2020 The lack of long-range dependence in convolutional neural networks causes weaker performance in generative adversarial networks(GANs) with regard to generating image details. The self-attention generative adversarial network(SAGAN) use the self-attention
Huan Li, Jinglei Tang
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Coevolution of Generative Adversarial Networks [PDF]
, 2019 Published in EvoApplications ...
Victor Costa +2 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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HGAN: Hybrid generative adversarial network [PDF]
Journal of Intelligent & Fuzzy Systems, 2021 In this paper, we present a simple approach to train Generative Adversarial Networks (GANs) in order to avoid a mode collapse issue. Implicit models such as GANs tend to generate better samples compared to explicit models that are trained on tractable data likelihood.
Seyed Mehdi Iranmanesh +1 more
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Survey of generative adversarial network
网络与信息安全学报, 2021 Firstly, the basic theory, application scenarios and current state of research of GAN (generative adversarial network) were introduced, and the problems need to be improved were listed. Then, recent research, improvement mechanism and model features in 2
WANG Zhenglong, ZHANG Baowen
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Slimmable Generative Adversarial Networks
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Generative adversarial networks (GANs) have achieved remarkable progress in recent years, but the continuously growing scale of models make them challenging to deploy widely in practical applications. In particular, for real-time generation tasks, different devices require generators of different sizes due to varying computing power.
Hou, Liang +5 more
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EvolGAN: Evolutionary Generative Adversarial Networks [PDF]
, 2021 We propose to use a quality estimator and evolutionary methods to search the latent space of generative adversarial networks trained on small, difficult datasets, or both. The new method leads to the generation of significantly higher quality images while preserving the original generator's diversity.
Roziere, Baptiste +6 more
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Text Generation Based on Generative Adversarial Nets with Latent Variable
, 2018 In this paper, we propose a model using generative adversarial net (GAN) to generate realistic text. Instead of using standard GAN, we combine variational autoencoder (VAE) with generative adversarial net. The use of high-level latent random variables is
Qin, Zengchang, Wan, Tao, Wang, Heng
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Training Generative Adversarial Networks With Weights [PDF]
2019 27th European Signal Processing Conference (EUSIPCO), 2019 The impressive success of Generative Adversarial Networks (GANs) is often overshadowed by the difficulties in their training. Despite the continuous efforts and improvements, there are still open issues regarding their convergence properties. In this paper, we propose a simple training variation where suitable weights are defined and assist the ...
Pantazis, Yannis +3 more
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Applied Sciences, 2023 This paper introduces a novel and robust data-driven algorithm designed for Aircraft Trajectory Prediction (ATP). The approach employs a Neural Network architecture to predict future aircraft trajectories, utilizing input variables such as latitude ...
Seyed Mohammad Hashemi +3 more
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