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Generative Adversarial Networks

2018
For 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
openaire   +1 more source

Generative Adversarial Network

2020
Generative adversarial networks (GANs) are a type of deep learning model designed by Ian Goodfellow and his colleagues in 2014.
openaire   +1 more source

Generative adversarial network

2021
Shih-Chia Huang, Trung-Hieu Le
openaire   +2 more sources

Convolutional Generative Adversarial Networks

2023
El 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, 2023
Damilola Adesina   +2 more
exaly  

Generative Adversarial Networks (GANs)

ACM Computing Surveys, 2022
Divya Saxena, Jiannong Cao
exaly  

Generative Adversarial Networks in Time Series: A Systematic Literature Review

ACM Computing Surveys, 2023
Eoin Brophy, Zhengwei Wang, Qi She
exaly  

Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain

ACM Computing Surveys, 2022
Ishai Rosenberg, Asaf Shabtai
exaly  

Generative Adversarial Networks in Computer Vision

ACM Computing Surveys, 2022
Zhengwei Wang
exaly  

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