Talk:DeepFace
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Wiki Education Foundation-supported course assignment
editThis article was the subject of a Wiki Education Foundation-supported course assignment, between 15 February 2021 and 15 May 2021. Further details are available on the course page. Student editor(s): Penguinblueberry. Peer reviewers: Stellasuperba, CelticsFan3, 99rebound, Hotpink789!, LowIQPotato, Luckyclover44.
Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 19:54, 17 January 2022 (UTC)
Bibliography
editBarrett, Lindsey. 2020. “Ban Facial Recognition Technologies for Children — and or everyone else” Journal of Science & Technology Law, p223-285, Asociacion Internacional de Galdosistas.,
Brinckerhoff, Rosie. 2018. “Social Network or Social Nightmare: How California Courts Cn Prevent Facebook’s Frightening Foray Into Facial Recognition Technology From Haunting Consumer Privacy Rights Forever.” Federal Communications Law Journal 70 Fed Comm. L.J. pp. 105-156. HEIN Online.
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Rosenthal, Sonny. 2020. “A tripartite model of trust in Facebook: acceptance of information personalization, privacy concern, and privacy literacy.” Media Psychology, Vol. 23 Issue 6, p840-864.
Trautman, Lawrence J. “Governance of the Facebook Privacy Crisis” Pittsburgh Journal of Technology Law and Policy, Vol. 20, pp. 43-147.
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Rubinstein, Ira S. 2013. “PRIVACY BY DESIGN: A COUNTERFACTUAL ANALYSIS OF GOOGLE AND FACEBOOK PRIVACY INCIDENTS.” Berkeley Technology Law Journal. Vol. 28 Issue 2.
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Lankton, Nancy K. 2017. “Facebook privacy management strategies: A cluster analysis of user privacy behaviors” In Computers in Human Behavior November. 76:149-163. — Preceding unsigned comment added by Penguinblueberry (talk • contribs) 05:58, 15 March 2021 (UTC)
Open Source Re-implementation
editThis edit request by an editor with a conflict of interest was declined. |
Even though the backbone of DeepFace model is shared from the research paper authored by Meta, its pre-trained weights is not released publicly. Still, some open source studies re-trained the model with publicly available datasets [1]. However, that open source re-implementation shows poor performance when compared to original study, with 69.0% score on LFW dataset [2]. Johncasey (talk) 11:37, 13 August 2024 (UTC) Johncasey (talk) 11:37, 13 August 2024 (UTC)
- We would need independent secondary sourcing to write about something like this, this isn't a place to take note of other implementations. - MrOllie (talk) 11:39, 13 August 2024 (UTC)
References
- ^ Sefik Ilkin Serengil. "DeepFace: A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python". GitHub. Retrieved 2024-08-12.
- ^ Serengil, Sefik; Ozpinar, Alper (2024). "A Benchmark of Facial Recognition Pipelines and Co-Usability Performances of Modules". Journal of Information Technologies. doi:10.17671/gazibtd.1399077.