Results 51 to 60 of about 222,297 (252)
International Journal of Digital Multimedia Broadcasting, 2021 The convolutional neural network has achieved good results in the superresolution reconstruction of single-frame images. However, due to the shortcomings of infrared images such as lack of details, poor contrast, and blurred edges, superresolution ...
Yuqing Zhao +4 more
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Improved Wasserstein conditional generative adversarial network speech enhancement
EURASIP Journal on Wireless Communications and Networking, 2018 The speech enhancement based on the generative adversarial network has achieved excellent results with large quantities of data, but performance in the low-data regime and tasks like unseen data learning still lag behind.
Shan Qin, Ting Jiang
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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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A quantum generative adversarial network for distributions [PDF]
Quantum Machine Intelligence, 2021 AbstractRecent advances in Quantum Computing have shown that, despite the absence of a fault-tolerant quantum computer so far, quantum techniques are providing exponential advantage over their classical counterparts. We develop a fully connected Quantum Generative Adversarial network and show how it can be applied in Mathematical Finance, with a ...
Amine Assouel +2 more
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Controllable Generative Adversarial Network
IEEE Access, 2019 Recently introduced generative adversarial networks (GANs) have been shown numerous promising results to generate realistic samples. In the last couple of years, it has been studied to control features in synthetic samples generated by the GAN. Auxiliary
Minhyeok Lee, Junhee Seok
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Towards Unsupervised Deep Image Enhancement With Generative Adversarial Network [PDF]
IEEE Transactions on Image Processing, 2020 Improving the aesthetic quality of images is challenging and eager for the public. To address this problem, most existing algorithms are based on supervised learning methods to learn an automatic photo enhancer for paired data, which consists of low ...
Zhangkai Ni +4 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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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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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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GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction [PDF]
Computer Vision and Pattern Recognition, 2019 In the past few years, a lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs).
Baris Gecer +3 more
semanticscholar +1 more source