Results 1 to 10 of about 6,226 (49)
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
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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
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Seismic random noise suppression using improved CycleGAN
Frontiers in Earth Science, 2023 Random noise adversely affects the signal-to-noise ratio of complex seismic signals in complex surface conditions and media. The primary challenges related to processing seismic data have always been reducing the random noise and increasing the signal-to-
Shimin Sun +8 more
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Time-Frequency Analysis and Target Recognition of HRRP Based on CN-LSGAN, STFT, and CNN
Complexity, 2021 Aiming at the problem of radar target recognition of High-Resolution Range Profile (HRRP) under low signal-to-noise ratio conditions, a recognition method based on the Constrained Naive Least-Squares Generative Adversarial Network (CN-LSGAN), Short-time ...
Jianghua Nie +3 more
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Mechanical and electrical equipment fault diagnosis based on dual attention mechanism and S-BiGAN
Hangkong gongcheng jinzhan, 2023 The accurate fault diagnosis of mechanical and electrical equipment under the condition of limited label samples is of great significance for improving the health management ability of complex mechanical and electrical equipment.
JIAO Xiaoxuan +4 more
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Multi-Stage Hybrid Text-to-Image Generation Models [PDF]
International Journal of Intelligent Computing and Information Sciences, 2022 Generative Adversarial Networks (GANs) have proven their outstanding potential in creating realistic images that can't differentiate between them and the real images, but text-to-image (conditional generation) still faces some challenges.
Razan Bayoumi +2 more
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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
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Recovery of Adversarial Examples Based on SmsGAN [PDF]
Zhengzhou Daxue xuebao. Gongxue ban, 2021 Due to adversarial examples′ serious interference to the detection models based on deep learning, a recovery method of adversarial examples based on stochastic multihlter statistical generative adversarial network (SmsGAN) was proposed in this work.
ZHAO Junjie, WANG Jinwei
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IEEE Access, 2020 With the appearance of Generative Adversarial Network (GAN), image-to-image translation based on a new unified framework has attracted growing interests.
Guifang Shao +4 more
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Technology in Cancer Research & Treatment, 2022 Purpose: To overcome the imaging artifacts and Hounsfield unit inaccuracy limitations of cone-beam computed tomography, a conditional generative adversarial network is proposed to synthesize high-quality computed tomography-like images from cone-beam ...
Yun Zhang PhD +6 more
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