About the MNIST database of handwritten digits

README.md

@@ -1,14 +1,25 @@
-# MatConvNet: CNNs for MATLAB
-
-**MatConvNet** is a MATLAB toolbox implementing *Convolutional Neural
-Networks* (CNNs) for computer vision applications. It is simple,
-efficient, and can run and learn state-of-the-art CNNs. Several
-example CNNs are included to classify and encode images. Please visit
-the [homepage](http://www.vlfeat.org/matconvnet) to know more.
-
-In case of compilation issues, please read first the
-[Installation](http://www.vlfeat.org/matconvnet/install/) and
-[FAQ](http://www.vlfeat.org/matconvnet/faq/) section before creating an GitHub
-issue. For general inquiries regarding network design and training
-related questions, please use the
-[Discussion forum](https://groups.google.com/d/forum/matconvnet).
+# Deep Hashing Network for Unsupervised Domain Adaptation
+
+In this work we propose a novel deep learning framework that can exploit 
+labeled source data and unlabeled target data to learn informative hash codes 
+to accurately classify unseen target data. To the best of our knowlege this 
+is the first  research effort to exploit the feature learning capabilities 
+of deep neural networks to learn representative hash codes to address the 
+domain adaptation problem. 
+
+We also introduce a new object recognition dataset **[Office-Home](https://hemanthdv.github.io/officehome-dataset/)** 
+for domain adaptation.
+
+The deep learning code is based off **MatConvNet** - a MATLAB toolbox 
+implementing *Convolutional Neural Networks* (CNNs) for computer vision 
+applications. Check out [homepage](http://www.vlfeat.org/matconvnet) to know more.
+
+The [paper](https://arxiv.org/pdf/1706.07522.pdf) can be cited using
+```
+@inproceedings{venkateswara2017Deep,
+  title={Deep Hashing Network for Unsupervised Domain Adaptation},
+  author={Venkateswara, Hemanth and Eusebio, Jose and Chakraborty, Shayok and Panchanathan, Sethuraman},
+  booktitle={IEEE} Conf. on Computer Vision and Pattern Recognition ({CVPR})},
+  year={2017}
+}
+```