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Generative Adversarial Networks
2018For many AI projects, deep learning techniques are increasingly being used as the building blocks for innovative solutions ranging from image classification to object detection, image segmentation, image similarity, and text analytics (e.g., sentiment analysis, key phrase extraction). GANs, first introduced by Goodfellow et al.
Mathew Salvaris +2 more
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Generative Adversarial Network
2020Generative adversarial networks (GANs) are a type of deep learning model designed by Ian Goodfellow and his colleagues in 2014.
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Enhancing generative adversarial network
Global Journal of Engineering and Technology AdvancesThe paper provides a comprehensive review of various GAN methods from the perspectives of theory, and applications. GAN algorithms' mathematical representations, and structures are detailed. The commonalities and differences among these GANs methods are compared.
Rajbeer Kaur +2 more
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Generative Adversarial Networks for Face Generation: A Survey
ACM Computing Surveys, 2022Amina Kammoun +4 more
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Adversarial Machine Learning in Wireless Communications Using RF Data: A Review
IEEE Communications Surveys and Tutorials, 2023Damilola Adesina +2 more
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Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain
ACM Computing Surveys, 2022Ishai Rosenberg, Asaf Shabtai
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A Survey on Generative Adversarial Networks: Variants, Applications, and Training
ACM Computing Surveys, 2022Songyuan Li
exaly
Generative Adversarial Networks in Time Series: A Systematic Literature Review
ACM Computing Surveys, 2023Eoin Brophy, Zhengwei Wang, Qi She
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