Added entry to superresolution section: Learning Iterative Image Reconstruction

This might be the earliest work on using hierarchical recurrent convolutional neural netwoks for computer vision tasks, such as superresolution and image denoising.

README.md

@@ -112,6 +112,9 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
 ### Low-Level Vision
 
 #### Super-Resolution
+* Iterative Image Reconstruction 
+  * Sven Behnke: Learning Iterative Image Reconstruction. IJCAI, 2001. [[Paper]](http://www.ais.uni-bonn.de/behnke/papers/ijcai01.pdf)
+  * Sven Behnke: Learning Iterative Image Reconstruction in the Neural Abstraction Pyramid. International Journal of Computational Intelligence and Applications, vol. 1, no. 4, pp. 427-438, 2001. [[Paper]](http://www.ais.uni-bonn.de/behnke/papers/ijcia01.pdf) 
 * Super-Resolution (SRCNN) [[Web]](http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html) [[Paper-ECCV14]](http://personal.ie.cuhk.edu.hk/~ccloy/files/eccv_2014_deepresolution.pdf) [[Paper-arXiv15]](http://arxiv.org/pdf/1501.00092.pdf)
   * Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang, Learning a Deep Convolutional Network for Image Super-Resolution, ECCV, 2014.
   * Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang, Image Super-Resolution Using Deep Convolutional Networks, arXiv:1501.00092.