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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 61–70 of 174 papers

TitleStatusHype
Pedestrian Attribute Editing for Gait Recognition and Anonymization—0
RiDDLE: Reversible and Diversified De-identification with Latent EncryptorCode1
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
Hiding Visual Information via Obfuscating Adversarial PerturbationsCode1
De-Identification of French Unstructured Clinical Notes for Machine Learning Tasks—0
DeID-VC: Speaker De-identification via Zero-shot Pseudo Voice ConversionCode1
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