Results 1 to 10 of about 116,908 (254)
Analysis and prediction of schizophrenia patients based on high-order graph attention generative adversarial networks [PDF]
Scientific ReportsGenerative Adversarial Networks, a popular deep learning method, have achieved excellent performance in both classification and prediction tasks. However, there have been relatively few applications of generative adversarial networks to EEG data.
Guimei Yin +11 more
doaj +2 more sources
Self-Sparse Generative Adversarial Networks
CAAI Artificial Intelligence Research, 2022 Generative adversarial networks (GANs) are an unsupervised generative model that learns data distribution through adversarial training. However, recent experiments indicated that GANs are difficult to train due to the requirement of optimization in the ...
Wenliang Qian +3 more
doaj +3 more sources
Conditional noise generative adversarial networks with Siamese neural network for longer time series forecasting [PDF]
Scientific ReportsGenerative adversarial networks have achieved strong results in computer vision, but their use in time series forecasting remains limited. This paper proposes a conditional noise generative adversarial network with a Siamese neural network as ...
Haotian Mao, Xiao Feng
doaj +2 more sources
Super-resolution Reconstruction of MRI Based on DNGAN [PDF]
Jisuanji kexue, 2022 The quality of MRI will affect doctor's judgment on patient's physical conditions,and the high-resolution MRI is more conducive to doctor to make an accurate diagnosis.Using computer technology to perform super-resolution reconstruction of MRI can obtain
DAI Zhao-xia, LI Jin-xin, ZHANG Xiang-dong, XU Xu, MEI Lin, ZHANG Liang
doaj +1 more source
IEEE Access, 2022 An adversarial example, which is an input instance with small, intentional feature perturbations to machine learning models, represents a concrete problem in Artificial intelligence safety.
Seok-Hwan Choi +3 more
doaj +1 more source
A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images
Remote Sensing, 2023 High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of super-resolution reconstruction of images is to reconstruct a given low-resolution ...
Xuan Wang +3 more
doaj +1 more source
Various Generative Adversarial Networks Model for Synthetic Prohibitory Sign Image Generation
Applied Sciences, 2021 A synthetic image is a critical issue for computer vision. Traffic sign images synthesized from standard models are commonly used to build computer recognition algorithms for acquiring more knowledge on various and low-cost research issues. Convolutional
Christine Dewi +3 more
doaj +1 more source
PEGANs: Phased Evolutionary Generative Adversarial Networks with Self-Attention Module
Mathematics, 2022 Generative adversarial networks have made remarkable achievements in generative tasks. However, instability and mode collapse are still frequent problems.
Yu Xue +3 more
doaj +1 more source
BoostNet: A Boosted Convolutional Neural Network for Image Blind Denoising
IEEE Access, 2021 Deep convolutional neural networks and generative adversarial networks currently attracted the attention of researchers because it is more effective than conventional representation-based methods.
Duc My Vo +3 more
doaj +1 more source
Constrained Generative Adversarial Networks
IEEE Access, 2021 Generative Adversarial Networks (GANs) are a powerful subclass of generative models. Yet, how to effectively train them to reach Nash equilibrium is a challenge.
Xiaopeng Chao +4 more
doaj +1 more source