Talk:DeepFace

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Wiki Education Foundation-supported course assignment

This 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)[reply]

Bibliography

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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)[reply]

Open Source Re-implementation

This 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)[reply]

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)[reply]

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.

[1] 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.

[2] 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.

[1]

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