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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 101–125 of 174 papers

TitleStatusHype
Smartphone Camera De-identification while Preserving Biometric Utility—0
Spanish Datasets for Sensitive Entity Detection in the Legal Domain—0
Speaker De-identification System using Autoencodersand Adversarial Training—0
Speaker Identification Experiments Under Gender De-Identification—0
StyleGAN as a Utility-Preserving Face De-identification Method—0
The Impact of De-identification on Downstream Named Entity Recognition in Clinical Text—0
The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project—0
The NLP Sandbox: an efficient model-to-data system to enable federated and unbiased evaluation of clinical NLP models—0
ToonerGAN: Reinforcing GANs for Obfuscating Automated Facial Indexing—0
Toward Face Biometric De-identification using Adversarial Examples—0
Towards a Data Privacy-Predictive Performance Trade-off—0
Towards De-identification of Legal Texts—0
Towards Privacy-Preserving Person Re-identification via Person Identify Shift—0
Towards Reversible De-Identification in Video Sequences Using 3D Avatars and Steganography—0
Towards the Creation of a Large Corpus of Synthetically-Identified Clinical Notes—0
Transferability of Neural Network Clinical De-identification Systems—0
Transfer Learning for Named-Entity Recognition with Neural Networks—0
Using routinely collected patient data to support clinical trials research in accountable care organizations—0
Utility Preservation of Clinical Text After De-Identification—0
VerA: Versatile Anonymization Applicable to Clinical Facial Photographs—0
Language Resources to Support Language Diversity – the ELRA Achievements—0
Privacy Protection in MRI Scans Using 3D Masked Autoencoders—0
A Comparative Evaluation Of Transformer Models For De-Identification Of Clinical Text Data—0
A Context-Enhanced De-identification System—0
A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation—0
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