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4 books on Image Generation [PDF]
Updated: May 12, 2024 | 29 |
Books on Image Generation offer indispensable knowledge and insights for startups venturing into the realm of AI-driven image creation. These resources provide a deep understanding of the underlying technologies, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), and how they can be harnessed to generate images, artwork, or other visual content. Additionally, these books delve into creative applications of image generation, from art and design to data augmentation for computer vision tasks. They often include practical techniques for fine-tuning models, data preprocessing, and generating high-quality images.
1. Mastering Image Creation with Midjourney AI Tools: How to Create Stunning AI Images with Midjourney
2023 by Renee Gade
"Mastering Image Creation with Midjourney AI Tools" stands as the definitive resource for individuals seeking to elevate their image creation endeavors. This comprehensive guide offers an in-depth exploration of Midjourney and its array of capabilities, encompassing both its free AI image generators and subscription-based tools. It immerses readers in the world of AI image generation, providing insights into each generator's unique features and empowering them to maximize performance for the creation of visually stunning images. The book offers a comprehensive understanding of Midjourney's potential while candidly addressing its limitations, offering step-by-step guidance for image creation. Practical tips and techniques, such as fine-tuning training data, are shared to enhance the reader's proficiency with these generators. Beyond technical insights, the book delves into the ethical dimensions of AI image creation, probing into concerns like potential biases in training data sets and the privacy implications inherent in AI-generated imagery, providing readers with a well-rounded perspective on this transformative technology.
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2. Image Generation
2023 by John Cayley
"Image Generation" presents a collection of John Cayley's initial texts, intentionally crafted to be fed into algorithmic systems for manipulation and generation. Within its pages, readers encounter printed renditions of the prose and poetry generated by these computational processes. In instances where the computation was designed to yield unpredictable results, the resulting language could have taken entirely divergent forms. These texts often serve as snapshots of a phenomenon that can also be perceived as an evolving process unfolding over time. The book supplements these creations with concise explanatory notes, providing insights into the underlying processes and methodologies.
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3. Generative Adversarial Networks for Image Generation
2021 by Xudong Mao, Qing Li
"Generative Adversarial Networks for Image Generation" begins with an exploration of Generative Adversarial Networks (GANs), introduced by Ian Goodfellow and collaborators, including Yoshua Bengio, in 2014, hailed by Yann Lecun, Facebook's AI research director, as "the most intriguing idea in machine learning in the last decade." The book offers a comprehensive overview of GANs, delving into the realm of image generation and providing intricate insights into the intricacies of GAN image generation. Furthermore, it examines various approaches to tackle the remaining challenges within GAN image generation. Additionally, the book explores the promising applications of GANs, encompassing image-to-image translation, unsupervised domain adaptation, and GANs' role in enhancing security. This book serves as an invaluable resource for students and researchers with interests in GANs, image generation, and the broader domains of machine learning and computer vision.
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4. Hands-On Image Generation with TensorFlow: A practical guide to generating images and videos using deep learning
2020 by Soon Yau Cheong
In "Hands-On Image Generation with TensorFlow," you'll embark on a practical journey that not only hones your image generation abilities but also fosters a robust comprehension of the underlying principles. Commencing with an introduction to the foundational concepts of image generation via TensorFlow, the book delves into Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs). As you progress, you'll master the art of constructing models tailored for diverse applications, including the creation of deepfake-based face swaps, neural style transfers, image-to-image translations, and the transformation of rudimentary images into photorealistic renditions. Moreover, you'll grasp the intricacies of constructing state-of-the-art deep neural networks, employing advanced techniques such as spectral normalization and self-attention layers, followed by exploration of advanced models for face manipulation and generation. The book extends its scope to encompass photo restoration, text-to-image synthesis, video retargeting, and neural rendering. Throughout this comprehensive guide, you'll gain hands-on experience in implementing an array of models from the ground up using TensorFlow 2.x, including PixelCNN, VAE, DCGAN, WGAN, pix2pix, CycleGAN, StyleGAN, GauGAN, and BigGAN.
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How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Mastering Image Creation with Midjourney AI Tools: How to Create Stunning AI Images with Midjourney
2023 by Renee Gade
"Mastering Image Creation with Midjourney AI Tools" stands as the definitive resource for individuals seeking to elevate their image creation endeavors. This comprehensive guide offers an in-depth exploration of Midjourney and its array of capabilities, encompassing both its free AI image generators and subscription-based tools. It immerses readers in the world of AI image generation, providing insights into each generator's unique features and empowering them to maximize performance for the creation of visually stunning images. The book offers a comprehensive understanding of Midjourney's potential while candidly addressing its limitations, offering step-by-step guidance for image creation. Practical tips and techniques, such as fine-tuning training data, are shared to enhance the reader's proficiency with these generators. Beyond technical insights, the book delves into the ethical dimensions of AI image creation, probing into concerns like potential biases in training data sets and the privacy implications inherent in AI-generated imagery, providing readers with a well-rounded perspective on this transformative technology.
Download PDF
2. Image Generation
2023 by John Cayley
"Image Generation" presents a collection of John Cayley's initial texts, intentionally crafted to be fed into algorithmic systems for manipulation and generation. Within its pages, readers encounter printed renditions of the prose and poetry generated by these computational processes. In instances where the computation was designed to yield unpredictable results, the resulting language could have taken entirely divergent forms. These texts often serve as snapshots of a phenomenon that can also be perceived as an evolving process unfolding over time. The book supplements these creations with concise explanatory notes, providing insights into the underlying processes and methodologies.
Download PDF
3. Generative Adversarial Networks for Image Generation
2021 by Xudong Mao, Qing Li
"Generative Adversarial Networks for Image Generation" begins with an exploration of Generative Adversarial Networks (GANs), introduced by Ian Goodfellow and collaborators, including Yoshua Bengio, in 2014, hailed by Yann Lecun, Facebook's AI research director, as "the most intriguing idea in machine learning in the last decade." The book offers a comprehensive overview of GANs, delving into the realm of image generation and providing intricate insights into the intricacies of GAN image generation. Furthermore, it examines various approaches to tackle the remaining challenges within GAN image generation. Additionally, the book explores the promising applications of GANs, encompassing image-to-image translation, unsupervised domain adaptation, and GANs' role in enhancing security. This book serves as an invaluable resource for students and researchers with interests in GANs, image generation, and the broader domains of machine learning and computer vision.
Download PDF
4. Hands-On Image Generation with TensorFlow: A practical guide to generating images and videos using deep learning
2020 by Soon Yau Cheong
In "Hands-On Image Generation with TensorFlow," you'll embark on a practical journey that not only hones your image generation abilities but also fosters a robust comprehension of the underlying principles. Commencing with an introduction to the foundational concepts of image generation via TensorFlow, the book delves into Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs). As you progress, you'll master the art of constructing models tailored for diverse applications, including the creation of deepfake-based face swaps, neural style transfers, image-to-image translations, and the transformation of rudimentary images into photorealistic renditions. Moreover, you'll grasp the intricacies of constructing state-of-the-art deep neural networks, employing advanced techniques such as spectral normalization and self-attention layers, followed by exploration of advanced models for face manipulation and generation. The book extends its scope to encompass photo restoration, text-to-image synthesis, video retargeting, and neural rendering. Throughout this comprehensive guide, you'll gain hands-on experience in implementing an array of models from the ground up using TensorFlow 2.x, including PixelCNN, VAE, DCGAN, WGAN, pix2pix, CycleGAN, StyleGAN, GauGAN, and BigGAN.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
