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Hands-On Image Generation with TensorFlow
Cód:
491_9781838826789

Por: R$ 353,75ou X de

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Implement various state-of-the-art architectures, such as GANs and autoencoders, for image generation using TensorFlow 2.x from scratchKey FeaturesUnderstand the different architectures for image generation, including autoencoders and GANsBuild models that can edit an image of your face, turn photos into paintings, and generate photorealistic imagesDiscover how you can build deep neural networks with advanced TensorFlow 2.x featuresBook DescriptionThe emerging field of Generative Adversarial Networks (GANs) has made it possible to generate indistinguishable images from existing datasets. With this hands-on book, youll 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. Youll 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. Youll 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. Youll also be introduced to photo restoration, text-to-image synthesis, video retargeting, and neural rendering. Throughout the book, youll 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, youll be well versed in TensorFlow and be able to implement image generative technologies confidently.What You Will LearnTrain 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 pi
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