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De-identification

De-identification is the task of detecting privacy-related entities in text, such as person names, emails and contact data.

Papers

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Showing 71–80 of 174 papers

TitleStatusHype
Disguise without Disruption: Utility-Preserving Face De-Identification—0
Development and validation of a natural language processing algorithm to pseudonymize documents in the context of a clinical data warehouse—0
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignmentCode0
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations—0
Pedestrian Attribute Editing for Gait Recognition and Anonymization—0
Toward Face Biometric De-identification using Adversarial Examples—0
Divide and Conquer: a Two-Step Method for High Quality Face De-identification with Model Explainability—0
StyleGAN as a Utility-Preserving Face De-identification Method—0
Privacy-Utility Balanced Voice De-Identification Using Adversarial Examples—0
An Easy-to-use and Robust Approach for the Differentially Private De-Identification of Clinical Textual Documents—0
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