Generative adversarial networks (GANs): An overview of theoretical model, evaluation metrics, and recent developments
One of the most significant challenges in statistical signal processing and machine learning
is how to obtain a generative model that can produce samples of large-scale data
distribution, such as images and speeches. Generative Adversarial Network (GAN) is an
effective method to address this problem. The GANs provide an appropriate way to learn
deep representations without widespread use of labeled training data. This approach has
attracted the attention of many researchers in computer vision since it can generate a large …
is how to obtain a generative model that can produce samples of large-scale data
distribution, such as images and speeches. Generative Adversarial Network (GAN) is an
effective method to address this problem. The GANs provide an appropriate way to learn
deep representations without widespread use of labeled training data. This approach has
attracted the attention of many researchers in computer vision since it can generate a large …
[引用][C] Generative adversarial networks (GANs): An overview of theoretical model, evaluation metrics, and recent developments. arXiv 2020
P Salehi, A Chalechale, M Taghizadeh - arXiv preprint arXiv:2005.13178
以上显示的是最相近的搜索结果。 查看全部搜索结果