SOTAVerified

De-identification

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–110 of 174 papers

TitleStatusHype
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
Show:102550
← PrevPage 11 of 18Next →

No leaderboard results yet.