國立虎尾科技大學 |

Face de-identification = safeguarding identities in the digital era /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Face de-identification/ by Yunqian Wen ... [et al.].
其他題名:	safeguarding identities in the digital era /
其他作者:	Wen, Yunqian.
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xviii, 188 p. :ill. (chiefly col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-031-58222-6
ISBN:	9783031582226

Face de-identification = safeguarding identities in the digital era /
Face de-identificationsafeguarding identities in the digital era /[electronic resource] :by Yunqian Wen ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xviii, 188 p. :ill. (chiefly col.), digital ;24 cm.

Introduction -- 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.

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.

ISBN: 9783031582226

Standard No.: 10.1007/978-3-031-58222-6doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: QA76.9.P735

Dewey Class. No.: 005.8

Face de-identification = safeguarding identities in the digital era /
LDR:03074nam a2200325 a 4500 001 1133669
003 DE-He213
005 20240706125235.0
006 m d
007 cr nn 008maaau
008 241213s2024 sz s 0 eng d
020 $a 9783031582226 $q (electronic bk.)
020 $a 9783031582219 $q (paper)
024 7 $a 10.1007/978-3-031-58222-6 $2 doi
035 $a 978-3-031-58222-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.P735
072 7 $a UYQP $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQP $2 thema
082 0 4 $a 005.8 $2 23
090 $a QA76.9.P735 $b F138 2024
245 0 0 $a Face de-identification $h [electronic resource] : $b safeguarding identities in the digital era / $c by Yunqian Wen ... [et al.].
260 $a Cham : $c 2024. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xviii, 188 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
505 0 $a Introduction -- 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 $a 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.
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Privacy. $3 575491
650 1 4 $a Automated Pattern Recognition. $3 1365734
650 0 $a Human face recognition (Computer science) $3 598555
650 0 $a Privacy-preserving techniques (Computer science) $3 1454935
700 1 $a Wen, Yunqian. $3 1454934
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-58222-6
950 $a Computer Science (SpringerNature-11645)