Results 1 to 10 of about 14,068,918 (254)
Generative Adversarial Network of Industrial Positron Images on Memory Module
Entropy, 2022 PET (Positron Emission Computed Tomography) imaging is a challenge due to the ill-posed nature and the low data of photo response lines. Generative adversarial networks have been widely used in computer vision and made great success recently.
Mingwei Zhu +3 more
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Applied Sciences, 2023 Global photographic aesthetic image generation aims to ensure that images generated by generative adversarial networks (GANs) contain semantic information and have global aesthetic feelings. Existing image aesthetic generation algorithms are still in the
Hua Zhang +4 more
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IEEE Access, 2023 Detecting anomalies is an essential task in many industries. Current state-of-the-art methods rely on a large number of parameters for high accuracy, which may not be suitable for implementing cost-effective real-time applications.
Akhrorjon Akhmadjon Ugli Rakhmonov +3 more
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Generate Cryptographic key using generated 3D- Digital Image [PDF]
Engineering and Technology Journal, 2009 Every few years, computer security has to re-invent itself. New technologies andnew application bring new threats, and force us to invent new protection mechanisms.Cryptography became important when businesses started to build networked computersystems ...
Hala B. Abdul Wahab +2 more
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Synthetic Traffic Sign Image Generation Applying Generative Adversarial Networks
Vietnam Journal of Computer Science, 2022 Recently, it was shown that convolutional neural networks (CNNs) with suitably annotated training data and results produce the best traffic sign detection (TSD) and recognition (TSR).
Christine Dewi +2 more
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Gender forgery of faces by fusing wavelet shortcut connection generative adversarial network
网络与信息安全学报, 2023 The mainstream methods in the field of facial attribute manipulation had the following two defects due to data and model architecture limitations.First, the bottleneck structure of the autoencoder model results in the loss of feature information, and the
Wanze CHEN +5 more
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SUGAN: A Stable U-Net Based Generative Adversarial Network
Sensors, 2023 As one of the representative models in the field of image generation, generative adversarial networks (GANs) face a significant challenge: how to make the best trade-off between the quality of generated images and training stability. The U-Net based GAN (
Shijie Cheng +4 more
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Image Generation of Tomato Leaf Disease Identification Based on Adversarial-VAE
Agriculture, 2021 The deep neural network-based method requires a lot of data for training. Aiming at the problem of a lack of training images in tomato leaf disease identification, an Adversarial-VAE network model for generating images of 10 tomato leaf diseases is ...
Yang Wu, Lihong Xu
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TextControlGAN: Text-to-Image Synthesis with Controllable Generative Adversarial Networks
Applied Sciences, 2023 Generative adversarial networks (GANs) have demonstrated remarkable potential in the realm of text-to-image synthesis. Nevertheless, conventional GANs employing conditional latent space interpolation and manifold interpolation (GAN-CLS-INT) encounter ...
Hyeeun Ku, Minhyeok Lee
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Sensors, 2022 Deep learning models have been used in several domains, however, adjusting is still required to be applied in sensitive areas such as medical imaging.
Halima Hamid N. Alrashedy +3 more
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