Description
Book SynopsisDeepfakes is a synthetic media that leverage powerful Artificial Intelligence (AI) and machine learning (ML) techniques to generate fake visual and audio content that are extremely realistic, thus making it very hard for a human to distinguish from the original ones. Apart from technological introduction to the Deepfakes concept, the book details algorithms to detect Deepfakes, techniques for identifying manipulated content and identifying face swap, generative adversarial neural networks, media forensic techniques, deep learning architectures, forensic analysis of DeepFakes and so forth.
- Provides a technical introduction to DeepFakes, its benefits, and the potential harms
- Presents practical approaches of creation and detection of DeepFakes using Deep Learning (DL) Techniques
- Draws attention towards various challenging issues and societal impact of DeepFakes with their existing solutions
- Includes research analysis in the domain of DL fakes for assisting the creation and detection of DeepFakes applications
- Discusses future research directions with emergence of DeepFakes technology
This book is aimed at graduate students, researchers and professionals in data science, artificial intelligence, computer vision, and machine learning.
Table of Contents1. Introduction to DeepFake technologies 2. DeepFakes: A Systematic Review and Bibliometric Analysis 3. Deep Learning Techniques for Creation of DeepFakes 4. Analyzing DeepFakes Videos by face warping artifacts 5. Development of image translating model to counter Adversarial attacks 6. Detection of DeepFakes using local features and Convolutional Neural Network 7. DeepFakes: Positive Cases 8. Threats and challenges by DeepFake Technology 9. DeepFakes, media, and societal impacts 10. Fake News Detection using Machine Learning 11. Future of DeepFakes & Ectypes
