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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Semi-supervised Learning on Graphs Using Adversarial Training with Generated Sample [PDF]
Jisuanji kexue yu tansuo, 2023 Given a graph composed of a small number of labeled nodes and a large number of unlabeled nodes, semi-supervised learning on graphs aims to assign labels for the unlabeled nodes.
WANG Cong, WANG Jie, LIU Quanming, LIANG Jiye
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Parametrization of stochastic inputs using generative adversarial networks with application in geology [PDF]
, 2019 We investigate artificial neural networks as a parametrization tool for stochastic inputs in numerical simulations. We address parametrization from the point of view of emulating the data generating process, instead of explicitly constructing a ...
Chan, Shing, Elsheikh, Ahmed H.
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Image Super-Resolution Reconstruction Algorithm Based on Generative Adversarial Networks [PDF]
Jisuanji gongcheng, 2021 The existing image Super-Resolution (SR) reconstruction algorithms have difficulty in network training and cause artifacts in the generated images.To address the problem,this paper proposes a SR reconstruction algorithm based on Generative Adversarial ...
JIANG Yuning, LI Jinhua, ZHAO Junli
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GAN and Chinese WordNet Based Text Summarization Technology [PDF]
Jisuanji kexue, 2022 Since the introduction of neural networks,text summarization techniques continue to attract the attention of resear-chers.Similarly,generative adversarial networks(GANs)can be used for text summarization because they can generate text features or learn ...
LIU Xiao-ying, WANG Huai, WU Jisiguleng
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Lung image segmentation via generative adversarial networks
Frontiers in PhysiologyIntroductionLung image segmentation plays an important role in computer-aid pulmonary disease diagnosis and treatment.MethodsThis paper explores the lung CT image segmentation method by generative adversarial networks.
Jiaxin Cai +4 more
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Recent Generative Adversarial Approach in Face Aging and Dataset Review
IEEE Access, 2022 Many studies have been conducted in the field of face aging, from approaches that use pure image-processing algorithms, to those that use generative adversarial networks.
Hady Pranoto +3 more
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A progressive growing of conditional generative adversarial networks model
Dianxin kexue, 2023 Progressive growing of generative adversarial networks (PGGAN) is an adversarial network model that can generate high-resolution images.However, when the categories of samples are unbalanced, or the categories of samples are too similar or too dissimilar,
Hui MA, Ruiqin WANG, Shuai YANG
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Generative Adversarial Optical Networks Using Diffractive Layers for Digit and Action Generation
PhotonicsWithin the traditional electronic neural network framework, Generative Adversarial Networks (GANs) have achieved extensive applications across multiple domains, including image synthesis, style transfer and data augmentation.
Pei Hu +3 more
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Super-Resolution for Overhead Imagery Using DenseNets and Adversarial Learning
, 2017 Recent advances in Generative Adversarial Learning allow for new modalities of image super-resolution by learning low to high resolution mappings.
Bosch, Marc +2 more
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