Generative Adversarial Networks (GANs) in networking: A comprehensive survey & evaluation [PDF]
Computer Networks, 2021 Accepted for publication at Journal of Computer ...
Hojjat Navidan +2 more
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On the Fairness of Generative Adversarial Networks (GANs) [PDF]
2021 International Conference "Nonlinearity, Information and Robotics" (NIR), 2021 Generative adversarial networks (GANs) are one of the greatest advances in AI in recent years. With their ability to directly learn the probability distribution of data, and then sample synthetic realistic data. Many applications have emerged, using GANs to solve classical problems in machine learning, such as data augmentation, class unbalance ...
Kenfack, Patrik Joslin +4 more
openaire +6 more sources
PTcomp: Post-Training Compression Technique for Generative Adversarial Networks
IEEE Access, 2023 In a time of virtual spaces, the usage of generative adversarial networks is inevitable. Generative adversarial networks (GANs) are generative deep-learning models that can generate realistic data.
Dina Tantawy +2 more
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Recent Progress on Generative Adversarial Networks (GANs): A Survey [PDF]
IEEE Access, 2019 Generative adversarial network (GANs) is one of the most important research avenues in the field of artificial intelligence, and its outstanding data generation capacity has received wide attention. In this paper, we present the recent progress on GANs.
Zhaoqing Pan +2 more
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GAN and Chinese WordNet Based Text Summarization Technology [PDF]
Jisuanji kexue, 2022 Since the introduction of neural networks,text summarization techniques continue to attract the attention of resear-chers.Similarly,generative adversarial networks(GANs)can be used for text summarization because they can generate text features or learn ...
LIU Xiao-ying, WANG Huai, WU Jisiguleng
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Variational Generative Adversarial Networks for Preventing Mode Collapse [PDF]
هوش محاسباتی در مهندسی برق, 2022 Generative models try to obtain a probability distribution that is similar to that of observed data. Two different solutions have been proposed in this regard in recent years: one is to minimize the divergence (distance) between the two distributions by ...
Mehdi Jamaseb Khollari +2 more
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Generative adversarial networks (GANS) for generating face images
Jurnal Ilmiah Kursor: Menuju Solusi Teknologi InformasiThe advancement of artificial intelligence technology, particularly deep learning, presents significant potential in facial image processing. Generative Adversarial Networks (GANs), a type of deep learning model, have demonstrated remarkable capabilities
Dolly Indra +2 more
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Insights and Considerations in Development and Performance Evaluation of Generative Adversarial Networks (GANs): What Radiologists Need to Know [PDF]
DiagnosticsJeong Taek Yoon +2 more
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Generative Adversarial Networks for the Synthesis of Chest X-ray Images
Engineering Proceedings, 2023 One way to diagnose COVID-19 is to use the Polymerase Chain Reaction (PCR) test. However, this test is rather invasive. An alternative would be to use chest images of the patients to diagnose if the patient has COVID-19.
Mai Feng Ng, Carol Anne Hargreaves
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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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