Jan 24, 2023 · In this paper, we present a system for detecting documents containing sensitive data, also in cases where they are intentionally hidden there.

Jun 4, 2024 · The article presents a method of document anonymization using generative adversarial neural networks. Unlike other anonymization methods, in the ...

We present a new approach to anonymizing personal data in text files. In the conducted research, an approach was applied that enables the analysis of ...

Privacy Preserving by Removing Sensitive Data from Documents with Fully Convolutional Networks ... Shin, H.C., et al.: Deep convolutional neural networks ...

We present a new approach to anonymizing personal data in text files. In the conducted research, an approach was applied that enables the analysis of.

In this paper, we propose a privacy-preserving deep learning framework that combines Instance Reduction Techniques (IR) and the Restricted Boltzmann Machine ( ...

Jun 29, 2024 · Given the sensitivity of medical images, ensuring privacy throughout the Deep Radiomics pipeline—from data generation and collection to model ...

This article presents a convolutional Bi-LSTM network to assess completely homomorphic-encrypted (HE) time-series medical images. From secret image sequences, ...

Oct 22, 2024 · Privacy Preserving by Removing Sensitive Data from Documents with Fully Convolutional Networks. January 2023 · Lecture Notes in Computer Science.

Apr 9, 2024 · ... remove sensitive information from the original data. A common approach used in machine learning involves masking the sensitive data ...