Faceswap
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Exploring Deepfakes
Master the innovative world of deepfakes and generative AI for face replacement with this full-color guide Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand what deepfakes are, their history, and how to use the technology ethically Get well-versed with the workflow and processes involved to create your own deepfakes Learn how to apply the lessons and techniques of deepfakes to your own problems Book DescriptionApplying Deepfakes will allow you to tackle a wide range of scenarios creatively. Learning from experienced authors will help you to intuitively understand what is going on inside the model. You’ll learn what deepfakes are and what makes them different from other machine learning techniques, and understand the entire process from beginning to end, from finding faces to preparing them, training the model, and performing the final swap. We’ll discuss various uses for face replacement before we begin building our own pipeline. Spending some extra time thinking about how you collect your input data can make a huge difference to the quality of the final video. We look at the importance of this data and guide you with simple concepts to understand what your data needs to really be successful. No discussion of deepfakes can avoid discussing the controversial, unethical uses for which the technology initially became known. We’ll go over some potential issues, and talk about the value that deepfakes can bring to a variety of educational and artistic use cases, from video game avatars to filmmaking. By the end of the book, you’ll understand what deepfakes are, how they work at a fundamental level, and how to apply those techniques to your own needs.What you will learn Gain a clear understanding of deepfakes and their creation Understand the risks of deepfakes and how to mitigate them Collect efficient data to create successful deepfakes Get familiar with the deepfakes workflow and its steps Explore the application of deepfakes methods to your own generative needs Improve results by augmenting data and avoiding overtraining Examine the future of deepfakes and other generative AIs Use generative AIs to increase video content resolution Who this book is for This book is for AI developers, data scientists, and anyone looking to learn more about deepfakes or techniques and technologies from Deepfakes to help them generate new image data. Working knowledge of Python programming language and basic familiarity with OpenCV, Pillow, Pytorch, or Tensorflow is recommended to get the most out of the book.
Generative AI for Cybersecurity
This book lays a systematic foundation for professionals, researchers, and industry readers who are interested the applications and implications of generative AI for cybersecurity. It covers the latest advances in generative AI and its applications, risks, and opportunities in cybersecurity. The authors first introduce the fundamental background of generative AI, the latest cybersecurity issues, and related potential applications in cybersecurity systems. Following this, they comprehensively review the state-of-the-art research and development, covering various aspects of generative AI applications in this area and related challenges and issues, such as training data availability, computational complexity, generalization to different scenarios, AI governance, quantum-empowered AI and many more. These discussions provide a strong understanding of recent advances in the two fields of generative AI and cybersecurity and the convergence of these domains, which will help readers to shape the field as it matures. Hands-on experiments presented throughout will also give them the practical skills for success. By leveraging its capabilities, readers can overcome challenges, understand the risks, enhance performance, and unlock new opportunities for handling the challenges of cybersecurity with generative AI. Consequently, they will be able to apply their knowledge to utilize generative AI in cybersecurity applications to prevent economic and other losses due to cyber risks such as phishing, fake news, deepfake-based fraud, and other cyberattacks. The contents of this book are appropriate for a wide range of readers from general readers to industry experts and scientists. Because it bridges the gap between generative AI and cybersecurity, experts from both fields will benefit from the information presented within. Students with a background in either area will also benefit from the approach that leads from general to specific applications.
Parallel and Distributed Computing, Applications and Technologies
This book constitutes the proceedings of the 22nd International Conference on Parallel and Distributed Computing, Applications, and Technologies, PDCAT 2021, which took place in Guangzhou, China, during December 17-19, 2021. The 24 full papers and 34 short papers included in this volume were carefully reviewed and selected from 97 submissions. The papers are categorized into the following topical sub-headings: networking and architectures, software systems and technologies, algorithms and applications, and security and privacy.