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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 81–90 of 174 papers

TitleStatusHype
DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation—0
Utility Preservation of Clinical Text After De-Identification—0
Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical TextsCode1
Improving speaker de-identification with functional data analysis of f0 trajectoriesCode0
A Comparative Evaluation Of Transformer Models For De-Identification Of Clinical Text Data—0
Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing—0
Radiology Text Analysis System (RadText): Architecture and EvaluationCode1
Speaker Identification Experiments Under Gender De-Identification—0
Digital Speech Algorithms for Speaker De-Identification—0
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text AnonymizationCode1
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