Results 11 to 20 of about 1,292,259 (284)

Person de-identification in activity videos [PDF]

2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014
Person identification based on gait recognition has been extensively studied in the last two decades, while information appearing in different action types (like bend) has been recently exploited to this end. However, in most application scenarios it is sufficient to recognize the performed activity, whereas the ID of persons performing activities is ...
Marina Ivasic-Kos, Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas   +3 more
openaire   +5 more sources

API Driven On-Demand Participant ID Pseudonymization in Heterogeneous Multi-Study Research [PDF]

Healthcare Informatics Research, 2021
Objectives To facilitate clinical and translational research, imaging and non-imaging clinical data from multiple disparate systems must be aggregated for analysis. Study participant records from various sources are linked together and to patient records
Shorabuddin Syed, Mahanazuddin Syed, Hafsa Bareen Syeda, Maryam Garza, William Bennett, Jonathan Bona, Salma Begum, Ahmad Baghal, Meredith Zozus, Fred Prior   +9 more
doaj   +1 more source

Person De-identification in Videos [PDF]

IEEE Transactions on Circuits and Systems for Video Technology, 2010
Advances in cameras and web technology have made it easy to capture and share large amounts of video data over to a large number of people through services like Google Street View, EveryScape, etc A large number of cameras oversee public and semi-public spaces today These raise concerns on the unintentional and unwarranted invasion of the privacy of ...
Prachi Agrawal, P. J. Narayanan
openaire   +1 more source

Protecting and Utilizing Health and Medical Big Data: Policy Perspectives from Korea [PDF]

Healthcare Informatics Research, 2019
ObjectivesWe analyzed Korea's data privacy regime in the context of protecting and utilizing health and medical big data and tried to draw policy implications from the analyses.MethodsWe conducted comparative analyses of the legal and regulatory ...
Dongjin Lee, Mijeong Park, Seungwon Chang, Haksoo Ko   +3 more
doaj   +1 more source

Guest Editorial: De‐identification [PDF]

IET Signal Processing, 2017
Privacy, described as "an integral part of our humanity" and "the beginning of all freedom", is one of the most important social and political issues in our information society. It is characterised by a growing range of enabling and supporting technologies and services such as communications, telemedicine, multimedia, biometrics, big data, the internet,
Ribarić, Slobodan, Ross, Arun
openaire   +2 more sources

Biometric Systems De-Identification: Current Advancements and Future Directions

Journal of Cybersecurity and Privacy, 2021
Biometric de-identification is an emerging topic of research within the information security domain that integrates privacy considerations with biometric system development.
Md Shopon, Sanjida Nasreen Tumpa, Yajurv Bhatia, K. N. Pavan Kumar, Marina L. Gavrilova   +4 more
doaj   +1 more source

Automatic Curation of Court Documents: Anonymizing Personal Data

Information, 2022
In order to provide open access to data of public interest, it is often necessary to perform several data curation processes. In some cases, such as biological databases, curation involves quality control to ensure reliable experimental support for ...
Diego Garat, Dina Wonsever
doaj   +1 more source

Building a best-in-class automated de-identification tool for electronic health records through ensemble learning

Patterns, 2021
Summary: The presence of personally identifiable information (PII) in natural language portions of electronic health records (EHRs) constrains their broad reuse.
Karthik Murugadoss, Ajit Rajasekharan, Bradley Malin, Vineet Agarwal, Sairam Bade, Jeff R. Anderson, Jason L. Ross, William A. Faubion, Jr., John D. Halamka, Venky Soundararajan, Sankar Ardhanari   +10 more
doaj   +1 more source

Pseudonymisation of neuroimages and data protection: Increasing access to data while retaining scientific utility

NeuroImage: Reports, 2021
For a number of years, facial features removal techniques such as ‘defacing’, ‘skull stripping’ and ‘face masking/blurring’, were considered adequate privacy preserving tools to openly share brain images.
Damian Eke, Ida E.J. Aasebø, Simisola Akintoye, William Knight, Alexandros Karakasidis, Ezequiel Mikulan, Paschal Ochang, George Ogoh, Robert Oostenveld, Andrea Pigorini, Bernd Carsten Stahl, Tonya White, Lyuba Zehl   +12 more
doaj   +1 more source

De-identification Without Losing Faces [PDF]

Proceedings of the ACM Workshop on Information Hiding and Multimedia Security, 2019
Training of deep learning models for computer vision requires large image or video datasets from real world. Often, in collecting such datasets, we need to protect the privacy of the people captured in the images or videos, while still preserve the useful attributes such as facial expressions.
Yuezun Li, Siwei Lyu
openaire   +2 more sources