Update readme.md

readme.md

@@ -133,17 +133,11 @@ The downloaded dataset folder contains
 # Example usage
 
 ## 1. Face recognition with masks
-Face recognition trained to usual face images have proven to give good accuracy.In the recent ongoing outbreak of Covid19, people have been advised to use face masks. With majority of people using face masks, the face recognition system fails to perform. Due to limited mask images, there is not enough masked data available to train a new system. MaskTheFace can be used to create masked data set from unmasked dataset which is then used to either fine-tune an existing or train a new face recognition system.
+Face recognition trained to usual face images have proven to give good accuracy. In the recent ongoing outbreak of Covid19, people have been advised to use face masks. With majority of people using face masks, the face recognition system fails to perform. Due to limited mask images, there is not enough masked data available to train a new system. MaskTheFace can be used to create masked data set from unmasked dataset which is then used to either fine-tune an existing or train a new face recognition system.
 
 ### Example
-A face recognition system consisting of 20 different classes was considered. A VGG16 network was trained on these 20 different classes of un-masked faces from VGGFace2 dataset for face recognition. The network achieved an accuracy of 68.3% on un-masked test dataset. When the same network was tested on the masked test images (obtained from MaskTheFace) gave an accuracy of only 36.6% (about half of that of before)
-
-MaskTheFace was used to convert the training dataset from previous problem to masked dataset. Both the unmasked and masked dataset was made a part of training set. The network trained on this dataset
-gave test accuracy of 70.7% on un-masked, while 65.5% on masked dataset.
-
-Not only the accuracy of masked dataset was improved, but the system also performed better on masked faces.
-
-![cover_photo](images/face_recognition.png)
+The paper below uses MaskTheFace for the application of masked face recognition and reports an increase of ∼38% in the true positive rate for the Facenet system. They also test the accuracy of re-trained system on the MFR2 dataset and report similar accuracy.
+[https://arxiv.org/pdf/2008.11104.pdf](https://arxiv.org/pdf/2008.11104.pdf)
 
 
 
@@ -156,7 +150,7 @@ The detector above was trained on 2000 images (1000 mask, 1000 without mask) fro
 ![cover_photo](images/mask_no_mask.png)
 
 ## 3. Classify masks
-
+MaskTheFace generated dataset can be used to classify among masks using a deep network.
 
 ## Citation
 If you find this repository useful, please use following citation