diff --git a/README.md b/README.md index a3abbd0..082ed30 100644 --- a/README.md +++ b/README.md @@ -68,7 +68,7 @@ for metric in metrics: **Ensemble learning for face recognition** - [`Demo`](https://youtu.be/EIBJJJ0ECXU) -A face recognition task can be handled by several models and similarity metrics. Herein, deepface offers a [special boosting and combination solution](https://sefiks.com/2020/06/03/mastering-face-recognition-with-ensemble-learning/) to improve the accuracy of a face recognition task. This provides a huge improvement on accuracy metrics but it runs much slower than single models. +A face recognition task can be handled by several models and similarity metrics. Herein, deepface offers a [special boosting and combination solution](https://sefiks.com/2020/06/03/mastering-face-recognition-with-ensemble-learning/) to improve the accuracy of a face recognition task. This provides a huge improvement on accuracy metrics. Human beings could have 97.53% score for face recognition tasks whereas this ensemble method passes the human level accuracy and gets 98.57% accuracy. On the other hand, this runs much slower than single models.