Update README.md

README.md

@@ -1,34 +1,28 @@
-# Caffe
+# Trained models
+https://drive.google.com/open?id=112OyHziceXoww6rZ_aIjTUzpKElg0sFd
 
-[![Build Status](https://travis-ci.org/BVLC/caffe.svg?branch=master)](https://travis-ci.org/BVLC/caffe)
-[![License](https://img.shields.io/badge/license-BSD-blue.svg)](LICENSE)
+(More discriptions will be updated soon.)
 
-Caffe is a deep learning framework made with expression, speed, and modularity in mind.
-It is developed by the Berkeley Vision and Learning Center ([BVLC](http://bvlc.eecs.berkeley.edu)) and community contributors.
-
-Check out the [project site](http://caffe.berkeleyvision.org) for all the details like
-
-- [DIY Deep Learning for Vision with Caffe](https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p)
-- [Tutorial Documentation](http://caffe.berkeleyvision.org/tutorial/)
-- [BVLC reference models](http://caffe.berkeleyvision.org/model_zoo.html) and the [community model zoo](https://github.com/BVLC/caffe/wiki/Model-Zoo)
-- [Installation instructions](http://caffe.berkeleyvision.org/installation.html)
-
-and step-by-step examples.
-
-[![Join the chat at https://gitter.im/BVLC/caffe](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/BVLC/caffe?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
-
-Please join the [caffe-users group](https://groups.google.com/forum/#!forum/caffe-users) or [gitter chat](https://gitter.im/BVLC/caffe) to ask questions and talk about methods and models.
-Framework development discussions and thorough bug reports are collected on [Issues](https://github.com/BVLC/caffe/issues).
-
-Happy brewing!
 
 ## License and Citation
 
 Caffe is released under the [BSD 2-Clause license](https://github.com/BVLC/caffe/blob/master/LICENSE).
 The BVLC reference models are released for unrestricted use.
 
-Please cite Caffe in your publications if it helps your research:
+Please cite these in your publications if this code helps your research:
 
+    @proceedins{huan2019increg,
+      Author = {Wang, Huan and Zhang, Qiming and Wang, Yuehai and Yu, Lu and Hu, Haoji},
+      Title = {Structured Pruning for Efficient ConvNets via Incremental Regularization},
+      Booktitle = {IJCNN},
+      Year = {2019}
+    }
+    @proceedins{huan2018spp,
+      Author = {Wang, Huan and Zhang, Qiming and Wang, Yuehai and Hu, Haoji},
+      Title = {Structured probabilistic pruning for convolutional neural network acceleration},
+      Booktitle = {BMVC},
+      Year = {2018}
+    }
     @article{jia2014caffe,
       Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
       Journal = {arXiv preprint arXiv:1408.5093},