Privacy-aware Tag Recommendation for Accurate Image Privacy Prediction

@article{Tonge2019PrivacyawareTR,
  title={Privacy-aware Tag Recommendation for Accurate Image Privacy Prediction},
  author={Ashwini Tonge and Cornelia Caragea},
  journal={ACM TIST},
  year={2019},
  volume={10},
  pages={40:1-40:28}
}
  • Ashwini Tonge, Cornelia Caragea
  • Published in TIST 2019
  • Computer Science
  • Online images’ tags are very important for indexing, sharing, and searching of images, as well as surfacing images with private or sensitive content, which needs to be protected. Social media sites such as Flickr generate these metadata from user-contributed tags. However, as the tags are at the sole discretion of users, these tags tend to be noisy and incomplete. In this article, we present a privacy-aware approach to automatic image tagging, which aims at improving the quality of user… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-8 OF 8 REFERENCES

    A New Baseline for Image Annotation

    VIEW 13 EXCERPTS
    HIGHLY INFLUENTIAL

    Fast Image Tagging

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Image annotation via graph learning

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL