diff --git a/CITATION.md b/CITATION.md index 0ab5c587..910ed297 100644 --- a/CITATION.md +++ b/CITATION.md @@ -10,13 +10,13 @@ If you use deepface in your research for facial recogntion purposes, please cite @article{serengil2024lightface, title = {A Benchmark of Facial Recognition Pipelines and Co-Usability Performances of Modules}, author = {Serengil, Sefik Ilkin and Ozpinar, Alper}, - journal = {Bilişim Teknolojileri Dergisi}, + journal = {Bilisim Teknolojileri Dergisi}, volume = {17}, number = {2}, - pages = {X–X}, + pages = {95-107}, year = {2024}, - doi = {10.17671/gazibtd.XXX}, - url = {XXX}, + doi = {10.17671/gazibtd.1399077}, + url = {https://dergipark.org.tr/en/pub/gazibtd/issue/84331/1399077}, publisher = {Gazi University} } ``` diff --git a/README.md b/README.md index d0b898c0..a627052a 100644 --- a/README.md +++ b/README.md @@ -349,13 +349,13 @@ If you use deepface in your research for facial recogntion purposes, please cite @article{serengil2024lightface, title = {A Benchmark of Facial Recognition Pipelines and Co-Usability Performances of Modules}, author = {Serengil, Sefik Ilkin and Ozpinar, Alper}, - journal = {Bilişim Teknolojileri Dergisi}, + journal = {Bilisim Teknolojileri Dergisi}, volume = {17}, number = {2}, - pages = {X–X}, + pages = {95-107}, year = {2024}, - doi = {10.17671/gazibtd.XXX}, - url = {XXX}, + doi = {10.17671/gazibtd.1399077}, + url = {https://dergipark.org.tr/en/pub/gazibtd/issue/84331/1399077}, publisher = {Gazi University} } ``` diff --git a/benchmarks/README.md b/benchmarks/README.md index 83405a90..fda37d60 100644 --- a/benchmarks/README.md +++ b/benchmarks/README.md @@ -8,10 +8,7 @@ You can reproduce the results by executing the `Perform-Experiments.ipynb` and ` ROC curves provide a valuable means of evaluating the performance of different models on a broader scale. The following illusration shows ROC curves for different facial recognition models alongside their optimal configurations yielding the highest accuracy scores. - -

In summary, FaceNet-512d surpasses human-level accuracy, while FaceNet-128d reaches it, with Dlib, VGG-Face, and ArcFace closely trailing but slightly below, and GhostFaceNet and SFace making notable contributions despite not leading, while OpenFace, DeepFace, and DeepId exhibit lower performance. @@ -113,4 +110,23 @@ Please note that humans achieve a 97.5% accuracy score on the same dataset. Conf | mediapipe |96.3 |90.0 |93.1 |89.3 |91.8 |64.8 |74.6 |77.6 |64.9 |61.6 | | ssd |**97.9** |97.0 |96.7 |96.6 |89.4 |91.5 |93.0 |69.9 |68.7 |63.8 | | opencv |96.2 |92.9 |95.8 |93.2 |91.5 |93.3 |91.7 |71.1 |68.1 |61.1 | -| skip |91.4 |67.6 |90.6 |54.8 |69.3 |78.4 |83.4 |57.4 |62.6 |61.1 | \ No newline at end of file +| skip |91.4 |67.6 |90.6 |54.8 |69.3 |78.4 |83.4 |57.4 |62.6 |61.1 | + +# Citation + +Please cite deepface in your publications if it helps your research - see [`CITATIONS`](https://github.com/serengil/deepface/blob/master/CITATION.md) for more details. Here is its BibTex entry: + +```BibTeX +@article{serengil2024lightface, + title = {A Benchmark of Facial Recognition Pipelines and Co-Usability Performances of Modules}, + author = {Serengil, Sefik Ilkin and Ozpinar, Alper}, + journal = {Bilisim Teknolojileri Dergisi}, + volume = {17}, + number = {2}, + pages = {95-107}, + year = {2024}, + doi = {10.17671/gazibtd.1399077}, + url = {https://dergipark.org.tr/en/pub/gazibtd/issue/84331/1399077}, + publisher = {Gazi University} +} +``` \ No newline at end of file