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Hands-On Image Generation with TensorFlow - A practical guide to generating images and videos using deep learning (Paperback)
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Hands-On Image Generation with TensorFlow - A practical guide to generating images and videos using deep learning (Paperback)
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Implement various state-of-the-art architectures, such as GANs and
autoencoders, for image generation using TensorFlow 2.x from
scratch Key Features Understand the different architectures for
image generation, including autoencoders and GANs Build models that
can edit an image of your face, turn photos into paintings, and
generate photorealistic images Discover how you can build deep
neural networks with advanced TensorFlow 2.x features Book
DescriptionThe emerging field of Generative Adversarial Networks
(GANs) has made it possible to generate indistinguishable images
from existing datasets. With this hands-on book, you'll not only
develop image generation skills but also gain a solid understanding
of the underlying principles. Starting with an introduction to the
fundamentals of image generation using TensorFlow, this book covers
Variational Autoencoders (VAEs) and GANs. You'll discover how to
build models for different applications as you get to grips with
performing face swaps using deepfakes, neural style transfer,
image-to-image translation, turning simple images into
photorealistic images, and much more. You'll also understand how
and why to construct state-of-the-art deep neural networks using
advanced techniques such as spectral normalization and
self-attention layer before working with advanced models for face
generation and editing. You'll also be introduced to photo
restoration, text-to-image synthesis, video retargeting, and neural
rendering. Throughout the book, you'll learn to implement models
from scratch in TensorFlow 2.x, including PixelCNN, VAE, DCGAN,
WGAN, pix2pix, CycleGAN, StyleGAN, GauGAN, and BigGAN. By the end
of this book, you'll be well versed in TensorFlow and be able to
implement image generative technologies confidently. What you will
learn Train on face datasets and use them to explore latent spaces
for editing new faces Get to grips with swapping faces with
deepfakes Perform style transfer to convert a photo into a painting
Build and train pix2pix, CycleGAN, and BicycleGAN for
image-to-image translation Use iGAN to understand manifold
interpolation and GauGAN to turn simple images into photorealistic
images Become well versed in attention generative models such as
SAGAN and BigGAN Generate high-resolution photos with Progressive
GAN and StyleGAN Who this book is forThe Hands-On Image Generation
with TensorFlow book is for deep learning engineers, practitioners,
and researchers who have basic knowledge of convolutional neural
networks and want to learn various image generation techniques
using TensorFlow 2.x. You'll also find this book useful if you are
an image processing professional or computer vision engineer
looking to explore state-of-the-art architectures to improve and
enhance images and videos. Knowledge of Python and TensorFlow will
help you to get the best out of this book.
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