Improve the "Understanding CNN" section

Made some improvements on the "Understanding CNN" section because all of the elements were listed two times. If the intention was to have lists and sub-lists then you just need to place a second star (*) in front of them.

README.md

@@ -216,17 +216,11 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
 ![understanding](https://cloud.githubusercontent.com/assets/5226447/8452083/1aaa0066-2023-11e5-800b-2248ead51584.PNG)
 (from Aravindh Mahendran, Andrea Vedaldi, Understanding Deep Image Representations by Inverting Them, CVPR, 2015.)
 
-* Equivariance and Equivalence of Representations [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Lenc_Understanding_Image_Representations_2015_CVPR_paper.pdf)
-* Karel Lenc, Andrea Vedaldi, Understanding image representations by measuring their equivariance and equivalence, CVPR, 2015.
-* Deep Neural Networks Are Easily Fooled [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Nguyen_Deep_Neural_Networks_2015_CVPR_paper.pdf)
-* Anh Nguyen, Jason Yosinski, Jeff Clune, Deep Neural Networks are Easily Fooled:High Confidence Predictions for Unrecognizable Images, CVPR, 2015.
-* Understanding Deep Image Representations by Inverting Them [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.pdf)
-* Aravindh Mahendran, Andrea Vedaldi, Understanding Deep Image Representations by Inverting Them, CVPR, 2015.
-* Object Detectors Emerge in Deep Scene CNNs [[Paper]](http://arxiv.org/abs/1412.6856)
-* Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba, Object Detectors Emerge in Deep Scene CNNs, ICLR, 2015.
-* Inverting Convolutional Networks with Convolutional Networks
+* Karel Lenc, Andrea Vedaldi, Understanding image representations by measuring their equivariance and equivalence, CVPR, 2015. [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Lenc_Understanding_Image_Representations_2015_CVPR_paper.pdf)
+* Anh Nguyen, Jason Yosinski, Jeff Clune, Deep Neural Networks are Easily Fooled:High Confidence Predictions for Unrecognizable Images, CVPR, 2015. [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Nguyen_Deep_Neural_Networks_2015_CVPR_paper.pdf) 
+* Aravindh Mahendran, Andrea Vedaldi, Understanding Deep Image Representations by Inverting Them, CVPR, 2015. [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.pdf)
+* Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba, Object Detectors Emerge in Deep Scene CNNs, ICLR, 2015. [[arXiv Paper]](http://arxiv.org/abs/1412.6856)
 * Alexey Dosovitskiy, Thomas Brox, Inverting Convolutional Networks with Convolutional Networks, arXiv, 2015. [[Paper]](http://arxiv.org/abs/1506.02753)
-* Visualizing and Understanding CNN
 * Matthrew Zeiler, Rob Fergus, Visualizing and Understanding Convolutional Networks, ECCV, 2014. [[Paper]](https://www.cs.nyu.edu/~fergus/papers/zeilerECCV2014.pdf)