000 | 04329nam a22005775i 4500 | ||
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001 | 978-3-031-58222-6 | ||
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008 | 240706s2024 sz | s |||| 0|eng d | ||
020 |
_a9783031582226 _9978-3-031-58222-6 |
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024 | 7 |
_a10.1007/978-3-031-58222-6 _2doi |
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_a006.4 _223 |
100 | 1 |
_aWen, Yunqian. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9105171 |
|
245 | 1 | 0 |
_aFace De-identification: Safeguarding Identities in the Digital Era _h[electronic resource] / _cby Yunqian Wen, Bo Liu, Li Song, Jingyi Cao, Rong Xie. |
250 | _a1st ed. 2024. | ||
264 | 1 |
_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2024. |
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300 |
_aXVIII, 188 p. 53 illus., 49 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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505 | 0 | _aIntroduction -- Facial Recognition Technology and the Privacy Risks -- Overview of Face De-identification Techniques -- Face Image Privacy Protection with Differential Private k-anonymity -- Differential Private Identification Protection for Face Images -- Personalized and Invertible Face De-identification -- High Quality Face De-identification with Model Explainability -- Deep Motion Flow Guided Reversible Face Video De-Identification -- Future Prospects and Challenges -- Conclusion. | |
520 | _aThis book provides state-of-the-art Face De-Identification techniques and privacy protection methods, while highlighting the challenges faced in safeguarding personal information. It presents three innovative image privacy protection approaches, including differential private k-anonymity, identity differential privacy guarantee and personalized and invertible Face De-Identification. In addition, the authors propose a novel architecture for reversible Face Video De-Identification, which utilizes deep motion flow to ensure seamless privacy protection across video frames. This book is a compelling exploration of the rapidly evolving field of Face De-Identification and privacy protection in the age of advanced AI-based face recognition technology and pervasive surveillance. This insightful book embarks readers on a journey through the intricate landscape of facial recognition, artificial intelligence, social network and the challenges posed by the digital footprint left behind by individuals in their daily lives. The authors also explore emerging trends in privacy protection and discuss future research directions. Researchers working in computer science, artificial intelligence, machine learning, data privacy and cybersecurity as well as advanced-level students majoring in computers science will find this book useful as reference or secondary text. Professionals working in the fields of biometrics, data security, software development and facial recognition technology as well as policymakers and government officials will also want to purchase this book. . | ||
650 | 0 |
_aPattern recognition systems. _93953 |
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650 | 0 |
_aData protection _xLaw and legislation. _923450 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 1 | 4 |
_aAutomated Pattern Recognition. _931568 |
650 | 2 | 4 |
_aPrivacy. _935098 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
700 | 1 |
_aLiu, Bo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9105174 |
|
700 | 1 |
_aSong, Li. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9105176 |
|
700 | 1 |
_aCao, Jingyi. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9105178 |
|
700 | 1 |
_aXie, Rong. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9105180 |
|
710 | 2 |
_aSpringerLink (Online service) _9105184 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031582219 |
776 | 0 | 8 |
_iPrinted edition: _z9783031582233 |
776 | 0 | 8 |
_iPrinted edition: _z9783031582240 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-58222-6 |
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