Update README.md

README.md

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 This repository contains all the evaluated models for which results are reported in the paper titled paper titled ["Understanding and Comparing Deep Neural Networks for Age and Gender Classification"](http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w23/Lapuschkin_Understanding_and_Comparing_ICCV_2017_paper.pdf) and published in the proceedings of the IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG) at the International Conference on Computer Vision (ICCV) 2017. 
 
 ![](pics/resultbarchart_sparse.png)
-*Model performances, depending on architecture, initialization and data preprocessing, averaged over all folds of the data set. For additional results, see section [Result Overview](https://github.com/sebastian-lapuschkin/understanding-age-gender-deep-learning-models/blob/master/README.md#result-overview)*
+*Model performances, depending on architecture, initialization and data preprocessing, averaged over all folds of the data set. For additional results, see section [Result Overview](https://github.com/sebastian-lapuschkin/understanding-age-gender-deep-learning-models/blob/master/README.md#result-overview).*
 
 That is, this repo contains the `deploy.prototxt` and `train_val.prototxt` files for all model architectures, pretraining and preprocessing choices for which performance measures are reported in the paper linked above.
 `mean.binaryproto` files for outright deploying the models using Caffe are supplied as well.