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Generative Adversarial Networks For Content Creation
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Download or read book GANs in Action written by Vladimir Bok and published by Simon and Schuster. This book was released on 2019-09-09 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Book Synopsis Generative Adversarial Networks for Image-to-Image Translation by : Arun Solanki
Download or read book Generative Adversarial Networks for Image-to-Image Translation written by Arun Solanki and published by Academic Press. This book was released on 2021-06-22 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images. - Introduces the concept of Generative Adversarial Networks (GAN), including the basics of Generative Modelling, Deep Learning, Autoencoders, and advanced topics in GAN - Demonstrates GANs for a wide variety of applications, including image generation, Big Data and data analytics, cloud computing, digital transformation, E-Commerce, and Artistic Neural Networks - Includes a wide variety of biomedical and scientific applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing, and disease diagnosis - Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable GANs for their applications
Book Synopsis Mastering Generative Adversarial Networks From Basics to Advanced Applications by : Nagaram Ramesh
Download or read book Mastering Generative Adversarial Networks From Basics to Advanced Applications written by Nagaram Ramesh and published by SGSH Publications. This book was released on 2024-08-11 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mastering Generative Adversarial Networks From Basics to Advanced Applications offers a thorough examination of Generative Adversarial Networks (GANs), covering their theoretical foundations, architectural innovations, and practical applications. This book delves into the original GAN model, its evolution, and the mathematical frameworks that support it, while also exploring cutting-edge variants and real-world use cases. Authored by Nagaram Ramesh and V. Bhargavi, it provides a crucial resource for academics, researchers, and practitioners aiming to deepen their understanding and effectively implement GAN technologies.
Book Synopsis Generative Adversarial Networks for Image Generation by : Xudong Mao
Download or read book Generative Adversarial Networks for Image Generation written by Xudong Mao and published by Springer Nature. This book was released on 2021-03-21 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative adversarial networks (GANs) were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook’s AI research director) as “the most interesting idea in the last 10 years in ML.” GANs’ potential is huge, because they can learn to mimic any distribution of data, which means they can be taught to create worlds similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and their output is remarkable – poignant even. In 2018, Christie’s sold a portrait that had been generated by a GAN for $432,000. Although image generation has been challenging, GAN image generation has proved to be very successful and impressive. However, there are two remaining challenges for GAN image generation: the quality of the generated image and the training stability. This book first provides an overview of GANs, and then discusses the task of image generation and the details of GAN image generation. It also investigates a number of approaches to address the two remaining challenges for GAN image generation. Additionally, it explores three promising applications of GANs, including image-to-image translation, unsupervised domain adaptation and GANs for security. This book appeals to students and researchers who are interested in GANs, image generation and general machine learning and computer vision.
Book Synopsis Generative Deep Learning by : David Foster
Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
Book Synopsis Human Interaction and Emerging Technologies by : Tareq Ahram
Download or read book Human Interaction and Emerging Technologies written by Tareq Ahram and published by Springer. This book was released on 2019-07-24 with total page 1027 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on research and developments in human-technology interaction. A special emphasis is given to human-computer interaction, and its implementation for a wide range of purposes such as healthcare, aerospace, telecommunication, and education, among others. The human aspects are analyzed in detail. Timely studies on human-centered design, wearable technologies, social and affective computing, augmented, virtual and mixed reality simulation, human rehabilitation and biomechanics represent the core of the book. Emerging technology applications in business, security, and infrastructure are also critically examined, thus offering a timely, scientifically-grounded, but also professionally-oriented snapshot of the current state of the field. The book is based on contributions presented at the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019, held on August 22-24, in Nice, France. It offers a timely survey and a practice-oriented reference guide to systems engineers, psychologists, sport scientists, physical therapists, as well as decision-makers, designing or dealing with the new generation of service systems. User Experience of a Social Media Based Knowledge Sharing System in Industry Work, Chapter of this book is available open access under a CC BY 4.0 license at link.springer.com
Book Synopsis Generative Adversarial Networks and Deep Learning by : Roshani Raut
Download or read book Generative Adversarial Networks and Deep Learning written by Roshani Raut and published by CRC Press. This book was released on 2023-04-10 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum
Book Synopsis Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation by : Sharma, Ramesh C.
Download or read book Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation written by Sharma, Ramesh C. and published by IGI Global. This book was released on 2024-02-07 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise of generative Artificial Intelligence (AI) signifies a momentous stride in the evolution of Large Language Models (LLMs) within the expansive sphere of Natural Language Processing (NLP). This groundbreaking advancement ripples through numerous facets of our existence, with education, AI literacy, and curriculum enhancement emerging as focal points of transformation. Within the pages of Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation, readers embark on a journey into the heart of this transformative phenomenon. Generative AI's influence extends deeply into education, touching the lives of educators, administrators, policymakers, and learners alike. Within the pages of this book, we explore the intricate art of prompt engineering, a skill that shapes the quality of AI-generated educational content. As generative AI becomes increasingly accessible, this comprehensive volume empowers its audience, by providing them with the knowledge needed to navigate and harness the potential of this powerful tool.
Book Synopsis Generative Adversarial Networks Projects by : Kailash Ahirwar
Download or read book Generative Adversarial Networks Projects written by Kailash Ahirwar and published by Packt Publishing Ltd. This book was released on 2019-01-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore various Generative Adversarial Network architectures using the Python ecosystem Key FeaturesUse different datasets to build advanced projects in the Generative Adversarial Network domainImplement projects ranging from generating 3D shapes to a face aging applicationExplore the power of GANs to contribute in open source research and projectsBook Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learnTrain a network on the 3D ShapeNet dataset to generate realistic shapesGenerate anime characters using the Keras implementation of DCGANImplement an SRGAN network to generate high-resolution imagesTrain Age-cGAN on Wiki-Cropped images to improve face verificationUse Conditional GANs for image-to-image translationUnderstand the generator and discriminator implementations of StackGAN in KerasWho this book is for If you’re a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.
Book Synopsis Hands-On Generative Adversarial Networks with Keras by : Rafael Valle
Download or read book Hands-On Generative Adversarial Networks with Keras written by Rafael Valle and published by Packt Publishing Ltd. This book was released on 2019-05-03 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop generative models for a variety of real-world use-cases and deploy them to production Key FeaturesDiscover various GAN architectures using Python and Keras libraryUnderstand how GAN models function with the help of theoretical and practical examplesApply your learnings to become an active contributor to open source GAN applicationsBook Description Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them. This book opens with an introduction to deep learning and generative models, and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that give you the ability to control characteristics of GAN outputs. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN. By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing. Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA What you will learnLearn how GANs work and the advantages and challenges of working with themControl the output of GANs with the help of conditional GANs, using embedding and space manipulationApply GANs to computer vision, NLP, and audio processingUnderstand how to implement progressive growing of GANsUse GANs for image synthesis and speech enhancementExplore the future of GANs in visual and sonic artsImplement pix2pixHD to turn semantic label maps into photorealistic imagesWho this book is for This book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a perfect mix of theory and hands-on content in order to implement GANs using Keras. Working knowledge of Python is expected.
Download or read book AI-generated Content written by Feng Zhao and published by Springer Nature. This book was released on 2023-12-03 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the revised selected papers of the First International Conference, AIGC 2023, held in Shanghai, China, during August 25–26, 2023 The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The volume focuses on the remarkable strides that have been made in the realm of artificial intelligence and its transformative impact on content creation. As delving into the content of the proceedings, the readers will encounter cutting-edge research findings, innovative applications, and thought-provoking insights that underscore the transformative potential of AI-generated content.
Book Synopsis Generative Adversarial Networks with Python by : Jason Brownlee
Download or read book Generative Adversarial Networks with Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-07-11 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step tutorials on generative adversarial networks in python for image synthesis and image translation.
Book Synopsis Graphical Models for Machine Learning and Digital Communication by : Brendan J. Frey
Download or read book Graphical Models for Machine Learning and Digital Communication written by Brendan J. Frey and published by MIT Press. This book was released on 1998 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description. #Includes bibliographical references and index.
Book Synopsis Generating a New Reality by : Micheal Lanham
Download or read book Generating a New Reality written by Micheal Lanham and published by Apress. This book was released on 2021-07-30 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects. By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new. What You Will Learn Know the fundamentals of content generation from autoencoders to generative adversarial networks (GANs) Explore variations of GAN Understand the basics of other forms of content generation Use advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2 Who This Book Is For Machine learning developers and AI enthusiasts who want to understand AI content generation techniques
Download or read book Psybersecurity written by Oliver Guidetti and published by CRC Press. This book was released on 2024-09-09 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Psybersecurity: Human Factors of Cyber Defence is a clarion call to action in the face of a stark reality: over 90% of cyberattacks exploit human vulnerabilities, as highlighted by the 2022 Global Risks Report from the World Economic Forum. This gap between the rapid advancement of cyber security technologies and the slower pace of development in human-centric defences poses a formidable challenge to national security and personal safety. Amidst the dazzling progress of AI technologies like ChatGPT and Microsoft Security Co-Pilot, the human element of cyber security remains critically underdeveloped. Set against the backdrop of the Australian government's ambitious goal to become the world's most cybersecure nation by 2030, this book embarks on a mission to address the overlooked human factors in cyber defence. It advocates for a balanced approach that not only relies on technological advancements but also significantly enhances the human aspects of cyber security. Through an interdisciplinary exploration, Psybersecurity delves into how cyberthreats exploit human vulnerabilities and offers innovative solutions for building resilience against these vulnerabilities. It examines the necessity for cyber security strategies that encompass psychological insights, systemic resilience, and the mitigation of human errors, particularly within critical infrastructures and cyber-physical systems (CPS). Furthermore, this work critiques existing cyber security education frameworks, proposing a comprehensive curriculum that equips individuals with technical skills and the behavioural competencies needed to navigate the cyber landscape ethically and effectively. It also addresses AI's ethical dilemmas and psychological impacts, offering a forward-looking perspective on combating AI-driven harassment and endorsing a new field of study: "Psybersecurity." Psybersecurity: Human Factors of Cyber Defence aims to bridge the gap between cyber security and human sciences, ignite a transformation in understanding, and fortify our digital world. It is an essential read for academics, professionals, and anyone committed to building a safer, more resilient cyber future in alignment with Australia's 2030 vision.
Book Synopsis Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices by : Gaur, Loveleen
Download or read book Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices written by Gaur, Loveleen and published by IGI Global. This book was released on 2024-10-10 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancement of generative artificial intelligence (AI) has brought about significant ethical challenges. As machines become more adept at creating human-like content, concerns about misuse, bias, privacy, and accountability have emerged. Without clear guidelines and regulations, there is a risk of unethical use, such as creating deepfake videos or disseminating misinformation, which could have severe societal consequences. Additionally, questions about intellectual property rights and the ownership of AI-generated creations still need to be solved, further complicating the ethical landscape. The book, Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices, comprehensively solves these ethical challenges. By providing insights into the historical development and key milestones of Generative AI, the book lays a foundation for understanding its complex ethical implications. It examines existing ethical frameworks and proposes new ones tailored to AI's unique characteristics, helping readers apply traditional ethics to AI development and deployment.
Book Synopsis Intelligent Information and Database Systems by : Ngoc Thanh Nguyen
Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2020-03-03 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 12033 and 11034 constitutes the refereed proceedings of the 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020, held in Phuket, Thailand, in March 2020. The total of 105 full papers accepted for publication in these proceedings were carefully reviewed and selected from 285 submissions. The papers of the first volume are organized in the following topical sections: Knowledge Engineering and Semantic Web, Natural Language Processing, Decision Support and Control Systems, Computer Vision Techniques, Machine Learning and Data Mining, Deep Learning Models, Advanced Data Mining Techniques and Applications, Multiple Model Approach to Machine Learning. The papers of the second volume are divided into these topical sections: Application of Intelligent Methods to Constrained Problems, Automated Reasoning with Applications in Intelligent Systems, Current Trends in Arti cial Intelligence, Optimization, Learning,and Decision-Making in Bioinformatics and Bioengineering, Computer Vision and Intelligent Systems, Data Modelling and Processing for Industry 4.0, Intelligent Applications of Internet of Things and Data AnalysisTechnologies, Intelligent and Contextual Systems, Intelligent Systems and Algorithms in Information Sciences, Intelligent Supply Chains and e-Commerce, Privacy, Security and Trust in Arti cial Intelligence, Interactive Analysis of Image, Video and Motion Data in LifeSciences.
