Evaluating the Impact of Face Anonymization Methods on Computer Vision Tasks: A Trade-Off Between Privacy and Utility
Data anonymization is an essential prerequisite that enables data sharing in a privacy-preserving manner. However, anonymization affects the quality of the data and thus might affect the performance of later conducted data analysis. In this work, we investigate the influence of different image-based...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10804775/ |
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