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Convolutional Generative Adversarial Networks
2023El objetivo de este trabajo es implementar tres modelos de redes GAN diferentes, como son la DCGAN, WGAN y WGAN-GP, para generar imágenes similares a las que conforman los datasets de MNIST y de CelebA. Para cada uno de los tres modelos se realizan cuatro entrenamientos, utilizando diferentes números de imágenes de los dos datasets para obtener una ...
Sánchez Hernández, Sergi +1 more
openaire +1 more source
Adversarial Machine Learning in Wireless Communications Using RF Data: A Review
IEEE Communications Surveys and Tutorials, 2023Damilola Adesina +2 more
exaly
A Survey on Generative Adversarial Networks: Variants, Applications, and Training
ACM Computing Surveys, 2022Songyuan Li
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Generative Adversarial Networks in Time Series: A Systematic Literature Review
ACM Computing Surveys, 2023Eoin Brophy, Zhengwei Wang, Qi She
exaly
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain
ACM Computing Surveys, 2022Ishai Rosenberg, Asaf Shabtai
exaly
A Survey on Adversarial Recommender Systems
ACM Computing Surveys, 2022Yashar Deldjoo, Tommaso Di Noia
exaly
How Generative Adversarial Networks and Their Variants Work
ACM Computing Surveys, 2020, Uiwon Hwang, Sungroh Yoon
exaly