Hands-on generative adversarial networks with Pytorch 1.x implement next-generation neural networks to build powerful GAN models using Python
"Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models Key Features Implement GAN architectures to generate images, text, audio, 3D models, and more Understand how GANs work and become an active contributor in the open source com...
| Otros Autores: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England ; Mumbai :
Packt
[2019]
|
| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630702406719 |
Tabla de Contenidos:
- Section 1. Introduction to GANs and PyTorch.Generative Adversarial Networks Fundamentals ; Getting Started with PyTorch 1.3 ; Best Practices for Model Design and Training-- Section 2. Typical GAN Models for Image Synthesis. Building Your First GAN with PyTorch ; Generating Images Based on Label Information ; Image-to-Image Translation and Its Applications ; Image Restoration with GANs ; Training Your GANs to Break Different Models ; Image Generation from Description Text ; Sequence Synthesis with GANs ; Reconstructing 3D models with GANs.
