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  • Data re-identification - Wikipedia
    Data re-identification or de-anonymization is the practice of matching anonymous data (also known as de-identified data) with publicly available information, or auxiliary data, in order to discover the person to whom the data belongs [1] This is a concern because companies with privacy policies, health care providers, and financial institutions may release the data they collect after the data
  • Practical and ready-to-use methodology to assess the re . . . - Nature
    Article Open access Published: 02 July 2025 Practical and ready-to-use methodology to assess the re-identification risk in anonymized datasets Louis Philippe Sondeck Maryline Laurent Scientific
  • Assessing and Minimizing Re-identification Risk in Research Data . . .
    Abstract Background: Sharing of research data derived from health system records supports the rigor and reproducibility of primary research and can accelerate research progress through secondary use But public sharing of such data can create risk of re-identifying individuals, exposing sensitive health information Method: We describe a framework for assessing re-identification risk that
  • Deep Learning for Person Re-identification: A Survey and Outlook
    Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increased interest in the computer vision community By dissecting the involved components in developing a person Re-ID system, we categorize it into
  • Reidentification - an overview | ScienceDirect Topics
    Reidentification is the assignment of the public name associated with a data record to the deidentified record Reidentification is sometimes necessary to verify the contents of a record or to provide information that is necessary for the well-being of the subject of a deidentified data record
  • Identifying Re-identification Challenges: Past, Current and Future . . .
    Liu X, Liu W, Mei T, Ma H Provid: progressive and multimodal vehicle reidentification for large-scale urban surveillance IEEE Trans Multimed 2017;20 (3):645–58
  • 【Re-ID】基于深度学习的Re-ID技术方法调研-CSDN博客
    Deep transfer learning for person reidentification [J] arXiv preprint arXiv:1611 05244, 2016 [2] Yutian Lin, Liang Zheng, Zhedong Zheng, YuWu, Yi Yang Improving person re-identification by attribute and identity learning [J] arXiv preprint arXiv:1703 07220, 2017 [3] Liang Zheng, Yi Yang, Alexander G Hauptmann
  • A Generative Approach to Person Reidentification - MDPI
    These images are sourced from the traditional Market1501 dataset [67], which we primarily used for our experiments Notably, we observe the significant similarity between different identities, underscoring the non-trivial nature of the reidentification problem Figure 9 Inherent clustering of the latent space
  • re-identification · GitHub Topics · GitHub
    pytorch re-identification person-reidentification light-reid-learning Updated on Sep 29, 2022 Python
  • Deep Transfer Learning for Person Re-Identification - IEEE Xplore
    Person re-identification (Re-ID) poses an inevitable challenge to deep learning: how to learn a robust deep model with millions of parameters on a small training set of few or no labels In this paper, two deep transfer learning methods are proposed to address the training data sparsity problem, respectively from the supervised and unsupervised settings First, a two-stepped fine-tuning





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