Results 1 to 10 of about 221,929 (334)
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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Efficient Geometry-aware 3D Generative Adversarial Networks [PDF]
Computer Vision and Pattern Recognition, 2021 Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge.
Eric Chan +11 more
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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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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
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Intriguing properties of synthetic images: from generative adversarial networks to diffusion models [PDF]
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 Detecting fake images is becoming a major goal of computer vision. This need is becoming more and more pressing with the continuous improvement of synthesis methods based on Generative Adversarial Networks (GAN), and even more with the appearance of ...
Riccardo Corvi +4 more
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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
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A Style-Based Generator Architecture for Generative Adversarial Networks [PDF]
Computer Vision and Pattern Recognition, 2018 We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. The new architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and ...
Tero Karras, S. Laine, Timo Aila
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Least Squares Generative Adversarial Networks [PDF]
IEEE International Conference on Computer Vision, 2016 Unsupervised learning with generative adversarial networks (GANs) has proven hugely successful. Regular GANs hypothesize the discriminator as a classifier with the sigmoid cross entropy loss function. However, we found that this loss function may lead to
Xudong Mao +5 more
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pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis [PDF]
Computer Vision and Pattern Recognition, 2020 We have witnessed rapid progress on 3D-aware image synthesis, leveraging recent advances in generative visual models and neural rendering. Existing approaches how-ever fall short in two ways: first, they may lack an under-lying 3D representation or rely ...
Eric Chan +4 more
semanticscholar +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
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