k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification
Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such data is the use of deidentification technique...
Main Authors: | Blaž Meden, Žiga Emeršič, Vitomir Štruc, Peter Peer |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-01-01
|
Series: | Entropy |
Subjects: | |
Online Access: | http://www.mdpi.com/1099-4300/20/1/60 |
Similar Items
-
Iris Deidentification With High Visual Realism for Privacy Protection on Websites and Social Networks
by: Mauro Barni, et al.
Published: (2021-01-01) -
Modified MRI Anonymization (De-Facing) for Improved MEG Coregistration
by: Ricardo Bruña, et al.
Published: (2022-10-01) -
ContexedNet: Context–Aware Ear Detection in Unconstrained Settings
by: Ziga Emersic, et al.
Published: (2021-01-01) -
Mathematics, risk, and messy survey data
by: Kristi Anne Thompson, et al.
Published: (2020-12-01) -
How to Correctly Detect Face-Masks for COVID-19 from Visual Information?
by: Borut Batagelj, et al.
Published: (2021-02-01)