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000 nam5i
001 2210080934491
003 DE-He213
005 20250321105408
007 cr nn 008mamaa
008 240706s2024 sz | s |||| 0|eng d
020 a97830315822269978-3-031-58222-6
024 a10.1007/978-3-031-58222-62doi
040 a221008
050 aQ337.5
050 aTK7882.P3
072 aUYQP2bicssc
072 aCOM0160002bisacsh
072 aUYQP2thema
082 a006.4223
100 aWen, Yunqian.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
245 00 aFace De-identification: Safeguarding Identities in the Digital Erah[electronic resource] /cby Yunqian Wen, Bo Liu, Li Song, Jingyi Cao, Rong Xie.
250 a1st ed. 2024.
264 aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.
300 aXVIII, 188 p. 53 illus., 49 illus. in color.bonline resource.
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
347 atext filebPDF2rda
505 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 aPattern recognition systems.
650 aData protectionxLaw and legislation.
650 aArtificial intelligence.
650 aAutomated Pattern Recognition.
650 aPrivacy.
650 aArtificial Intelligence.
700 aLiu, Bo.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
700 aSong, Li.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
700 aCao, Jingyi.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
700 aXie, Rong.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
710 aSpringerLink (Online service)
773 tSpringer Nature eBook
776 iPrinted edition:z9783031582219
776 iPrinted edition:z9783031582233
776 iPrinted edition:z9783031582240
856 uhttps://doi.org/10.1007/978-3-031-58222-6
912 aZDB-2-SCS
912 aZDB-2-SXCS
950 aComputer Science (SpringerNature-11645)
950 aComputer Science (R0) (SpringerNature-43710)
Face De-identification: Safeguarding Identities in the Digital Era[electronic resource] /by Yunqian Wen, Bo Liu, Li Song, Jingyi Cao, Rong Xie
Material type
전자책
Title
Face De-identification: Safeguarding Identities in the Digital Era[electronic resource] /by Yunqian Wen, Bo Liu, Li Song, Jingyi Cao, Rong Xie
Author's Name
Liu Bo. author Song Li. author Cao Jingyi. author Xie Rong. author
판 사항
1st ed. 2024.
Physical Description
XVIII, 188 p 53 illus, 49 illus in color online resource.
Keyword
This 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. .
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CPriority Cataloging
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