Listing 1 - 4 of 4 |
Sort by
|
Choose an application
From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning---especially when it comes to discerning the truth and differentiating fact from fiction. This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias which gets amplified in harmful data feedback loops. Dont be afraid: with this book youll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope.
Fake news --- Deepfakes --- Computer algorithms. --- Prevention. --- Algorithms --- Deep fakes --- Deepfake AI --- Disinformation --- Forgery --- News, Fake --- Hoaxes --- Journalism --- Social media. --- User-generated media --- Communication --- User-generated content
Choose an application
"The first comprehensive introduction to the significance of deepfakes"--
#SBIB:309H1730 --- #SBIB:309H162 --- #SBIB:309H103 --- Artificiële Intelligentie, knowledge engineering, --- Videogrammen: functies, genres, historiek --- Mediatechnologie / ICT / digitale media: sociale en culturele aspecten --- Deepfakes --- Information technology --- Disinformation --- Social aspects.
Choose an application
This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.
Biometric identification. --- Deepfakes. --- Image processing --- Morphing (Computer animation). --- Digital techniques. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification --- Computer-generated metamorphosis --- Metamorphosing (Computer animation) --- Computer animation --- Digital image processing --- Digital electronics --- Deep fakes --- Deepfake AI --- Disinformation --- Forgery --- DeepFakes --- Face Manipulation Detection --- Media Forensic --- Biometric Recognition --- Image Processing and Pattern Recognition --- Open Access
Choose an application
This book is an open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field
Digital forensic science. --- Multimedia systems. --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Computer and network forensics --- Computer forensics --- Digital forensics --- Network forensics --- Electronic evidence --- Forensic sciences --- Digital preservation --- Media Forensics --- Digital Image Forensics --- Video Forensics --- Sensor Noise (PRNU) --- Deepfakes --- Digital Integrity --- Video Tampering Detection --- Image Tampering Detection --- ENF --- Counter-Forensics
Listing 1 - 4 of 4 |
Sort by
|