Multimedia forensics / / editors, Husrev T. Sencar, Luisa Verdoliva, Nasir D. Memon.
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 applicati...
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Superior document: | Advances in computer vision and pattern recognition |
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TeilnehmendeR: | |
Year of Publication: | 2022 |
Language: | English |
Series: | Advances in computer vision and pattern recognition
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Physical Description: | 1 online resource (xii, 490 pages) :; illustrations (some color). |
Notes: | Description based upon print version of record. |
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245 | 1 | 0 | |a Multimedia forensics / |c editors, Husrev T. Sencar, Luisa Verdoliva, Nasir D. Memon. |
260 | |a Singapore : |b Springer, |c 2022. | ||
300 | |a 1 online resource (xii, 490 pages) : |b illustrations (some color). | ||
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338 | |a online resource |b cr |2 rdacarrier | ||
490 | 1 | |a Advances in computer vision and pattern recognition | |
505 | 0 | |a What's In This Book and Why? Media Forensics in the Age of Disinformation Computational Imaging Sensor Fingerprints: Camera Identification and Beyond Source Camera Attribution from Videos Source Camera Model Identification GAN Fingerprints in Face Image Synthesis Physical Integrity | |
520 | |a 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 | ||
500 | |a Description based upon print version of record. | ||
546 | |a English | ||
650 | 0 | |a Digital forensic science. | |
650 | 0 | |a Multimedia systems. | |
653 | |a Media Forensics | ||
653 | |a Digital Image Forensics | ||
653 | |a Video Forensics | ||
653 | |a Sensor Noise (PRNU) | ||
653 | |a Deepfakes | ||
653 | |a Digital Integrity | ||
653 | |a Video Tampering Detection | ||
653 | |a Image Tampering Detection | ||
653 | |a ENF | ||
653 | |a Counter-Forensics | ||
700 | 1 | |a Sencar, Husrev T. | |
776 | 1 | |z 981-16-7620-8 | |
700 | 1 | |a Verdoliva, Luisa. | |
700 | 1 | |a Memon, Nasir D. | |
830 | 0 | |a Advances in computer vision and pattern recognition | |
906 | |a BOOK | ||
ADM | |b 2023-05-20 14:26:12 Europe/Vienna |f system |c marc21 |a 2022-04-02 22:03:30 Europe/Vienna |g false | ||
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